Alan Stanley
Wed, 11/03/2021 - 07:04
Edited Text

Paul Bernard Lemieux

A thesis submitted in partial fulfillment of the requirements
for graduation with Honors in Individually Planned Major: Global Health

Whitman College

Certificate of Approval

This is to certify that the accompanying thesis by Paul Bernard Lemieux
has been accepted in partial fulfillment of the requirements
for graduation with Honors in Individually Planned Major: Global Health

Jason Pribilsky
Department of Anthropology







































The coevolution of humans and the malaria-causing plasmodium protozoa has
taken place over millennia, with human history being shaped by malaria since its
beginnings. Over time, malaria has had one of the highest impacts on human mortality of
all diseases, an impact that continues into the present. In 2012, the World Health
Organization (WHO) estimated 207 million cases of malaria occurred globally, with an
estimated 627,000 deaths due to the disease. 3.3 billion people live in malaria endemic
regions, close to half the world’s population. The burden of malaria extends beyond
health into development and economic growth, where malaria plays a significant role in
stagnating economies and impaired development (Datta & Reimer 2013). The greatest
burden of malaria is in Sub-Saharan Africa, where 80% of cases and 90% of deaths
occur. Children under 5 constitute 85% of malaria patients and 77% of fatalities
(Anthony et al. 2012, WHO World Malaria Report 2013).
As a result of widespread malaria control efforts throughout the 1950’s and
1960’s, the elimination of malaria in many regions became increasingly attainable and
significant progress was made before first-line antimalarial drugs such as chloroquine lost
efficacy due to the spread of resistance. The current first-line treatment for malaria is
artemisinin-based combination therapy (ACT), a combination of a derivative of the
artemisinin compound paired with one of multiple partner drugs. The recent emergence
of resistance to artemisinins threatens to reverse the progress achieved in the past decades
in multimillion-dollar malaria control and elimination projects and looms as a potential
disaster in the impact of resistant malaria on the loss of human life. Consequently, the

containment of artemisinin resistance has quickly become a top priority for governments
of endemic countries, multinational organizations, and nonprofits working in the malaria
In 2011, the World Health Organization issued the Global Plan for Artemisinin
Resistance Containment (GPARC). The plan outlines the following five goals for the
containment of artemisinin-resistant malaria:
1. Stop the spread of resistant parasites
2. Increase monitoring and surveillance to evaluate the artemisinin resistance
3. Improve access to diagnostics and rational treatment with ACTs
4. Invest in artemisinin resistance-related research
5. Motivate action and mobilize resources (Global Plan for Artemisinin
Resistance Containment 2011).
The GPARC is intended as a general framework; much of the specific detail of how
strategies will be implemented is not elaborated upon, as specifics are understood to
change by location and over time. As such, there are challenges to the achievement of
these goals that are not addressed in the GPARC that should be considered in order to
ensure adequate and efficient use of resources. The aim of this work is to address these
subtler challenges, building upon a faceted and thorough understanding of malaria
genetics and epidemiology. With this understanding, the work presents the challenges in
containment and recommends a multifaceted and evidence-based strategy—including
attention to improved surveillance, diagnosis, prevention, treatment, and collaboration
strategies—to best contain artemisinin resistance. In the short-term and with the current
tools at our disposal, the two components of collaboration between stakeholders and
project funding have the potential for the most progress and are fundamental to all
containment efforts. The WHO reported a funding gap of between $300 and $350 million


in containment efforts, a deficit that if left unfilled will be detrimental to resistance
containment in the GMS. Although current strategies in the GMS are based on the latest
evidence and employing effective diagnostics and treatments, increased funding and
collaboration could strengthen malaria containment and increase efficiency in malaria
projects, improving the outcomes of containment efforts. The success of these efforts,
however, is difficult to measure accurately, as the spread of artemisinin resistance is still
not clear. With the recent discovery of a molecular marker of resistance and with the
development of rapid and mobile immunoassays in the near future, understandings of the
containment of resistance and the efficacies of various strategies will become more
The following analysis begins with a discussion of malaria biology and the
complex malaria lifecycle in the first chapter. The second chapter provides a framework
for artemisinins in the recent history of antimalarials, discussing the importance of
artemisinins, including how characteristics such as their fast action and excellent safety
profile have contributed to their prominence as partner drugs in first-line, antimalarial
combinations. The importance of standardized metrics for defining antimalarial and
artemisinin resistance and the debate over these metrics are discussed in the third chapter,
highlighting the necessity of standard metrics for coordinated resistance containment
efforts. The fourth chapter provides an analysis of the multiple factors, including both
biological as well as pharmaceutical and other human-caused factors, that affect the
speed at which resistant mutations arise and spread. This analysis of factors then focuses
on the Greater Mekong Subregion (GMS) in the fifth chapter, the region in which
artemisinin resistance has been found, discussing the region’s history with the


development of resistance to previous antimalarials as well as analyzing potential factors
specific to the region that could contribute to the development of resistance. The sixth
chapter analyzes current containment strategies and some of the principal challenges
associated with each, followed by a chapter focused on the two areas in which immediate
improvement could be made: the issues of collaboration and funding.


A foundation of the biology, genetics, and epidemiology involved in the
development and spread of resistance is critical in order to ensure containment strategies
are founded in a realistic understanding of the spread of malaria. In this way,
foundational knowledge of malaria biology and the pharmacokinetics of ACTs is a
critical precursor to advising optimal strategies for resistance containment and
Malaria in humans is caused by five species of the Plasmodium genus: P.
falciparum, P. vivax, P. ovale, P. knowlesi, and P. malariae. Falciparum and vivax are
responsible for the majority of malaria cases, with falciparum malaria associated with the
most severe forms of malaria and the highest number of fatalities, particularly in SubSaharan Africa. The plasmodium lifecycle is complex and dependent both on the human
host and the mosquito vector, as particular stages of the Plasmodium lifecycle are specific
to both. Gametocyte development takes place within the mosquito, while the majority of
asexual reproduction takes place within the human host. The parasite enters the human
through the mosquito’s saliva, injected preliminarily into the human and containing anti-


coagulants necessary for the mosquito to take its subsequent blood meal. Plamodium
enters the human bloodstream in the form of sporozoites, which make their way to the
liver where they invade human hepatocytes. In the liver, the parasite undergoes a stage of
multiple, asexual reproductions, forming merozoites. In vivax and ovale malaria species,
not all of the Plasmodium protozoa enter this stage immediately and some stay dormant
in the hepatocytes, protected inside the cell. These hypnozoites, the dormant, liver-stage
parasites, replicate up to four years later, causing a relapse of symptoms.
Once a critical number of merozoites are formed within a hepatocyte, the cell
ruptures, releasing the merozoites into the bloodstream. In the bloodstream, merozoites
invade erythrocytes and form a ‘ring-form’ trophozoite within the red blood cells. The
trophozoite undergoes nuclear division without cytokinesis, forming a multinucleated
schizont. In this stage of rapid reproduction, the parasite uses proteolysis to degrade host
hemoglobin into amino acids for its own metabolic needs (Mita & Tanabe 2012).
Cytokinesis forms distinct merozoites, which eventually rupture the erythrocyte, causing
the symptoms of malaria. The merozoites invade other, healthy erythrocytes, continuing
the cycle and worsening the malarial symptoms. In cases of a natural cure, untreated
infections last an average of 200 days, although they can last much longer (Klein 2013).
Clinical immunity to malaria develops with repeated exposure. In non-immune patients,
symptoms of malaria typically occur at parasitemia levels of greater than 50 parasites per
µL blood, which in adults constitutes between 108 and 109 total parasites. Regardless of
clinical immunity, most patients are symptomatic at levels above 1011 total parasites or
10,000 parasites per µL blood (Klein 2013). Consequently, the highest levels of clinical
immunity are found in areas of high transmission. When infected, immune individuals


have lower parasitemia levels and as a result are often asymptomatic. Treatment is also
often more effective in immune individuals versus non-immune. However, because
immune individuals still have some levels of parasitemia, they are still able to transmit
malaria when bitten by an uninfected mosquito.
Malarial transmission is accomplished through a subset of trophozoites in the
bloodstream, which, instead of undergoing nuclear division, form micro- and
macrogametocytes. Thus, when an uninfected mosquito takes blood from an infected
human, transmission continues when the mosquito takes up these gametocytes, which
within the mosquito join to form a zygote. The zygote forms an ookinete, which
penetrates the gut epithelial cells of the mosquito and forms an oocyst. Within the oocyst,
sporozoites form, eventually rupturing the oocyst and making their way to the mosquito’s
salivary glands, completing the cycle.
The complexity of the malaria lifecycle is an important factor in the rate of
antimalarial development, as drugs are often effective on multiple life stages of
Plasmodium. As such, effective antimalarials require drug targets that are present in
multiple stages, and differences between malarial life stages can affect antimalarial

Malarial transmission is dependent on both the human host and the mosquito
vector. Consequently, environmental, behavioral and genetic factors of the vector have a
direct impact on transmission. Malaria is spread through the anopheles mosquito, a genus
that comprises more than 400 species. Of these, over 100 species can transmit malaria to
humans, although only roughly 30 are of major importance as vectors. The different


vector species have differing breeding habits, lifecycles, ecological niches, feeding
behaviors, and susceptibilities to Plasmodium infection, each affecting malarial
transmission differently. Anopheles on average live within a range of 1 km from where
they breed, demonstrating that human movement is often the more significant factor in
the spread of resistance across large areas, as discussed further on. Moreover, the lifespan
of most mosquitoes is around 10 days, whereas a malarial infection in humans on average
lasts 200 days (Klein 2013). An. gambiae is a complex of several species consisting of
many of the most important vectors for malaria and is responsible for much of the P.
falciparum transmission in Sub-Saharan Africa.


The Artemisia genus, comprising multiple species of shrubs native to temperate
areas of the northern hemisphere and South America, has been used for more than 2,000
years in traditional Chinese medicine (Liu et al. 2013), making it the oldest, known usage
of an antimalarial. The second oldest, quinine, which is derived from the bark of the
cinchona tree, has been used since the early 1600’s for the treatment of fevers (Shah &
Seth 2010). Since then, the malaria field has seen the inevitable rise of resistance to all
previously used antimalarials, although resistance has arisen and spread at different rates
depending on usage. Several antimalarials were successively used as first-line treatments
in international campaigns for malaria control in the second half of the 20th century,
starting with chloroquine and followed by the synergistic combination sulfadoxinepyrimethamine. Policies based on a limited understanding of the mechanisms of drug


resistance contributed to control strategies that rapidly selected for drug-resistant strains.
The prime example, using both chloroquine and sufladoxine-pyrimethamine, was the
widespread distribution of table salt mixed with subtherapeutic antimalarial dosages as a
control strategy, as discussed in the fifth chapter. With the rapid spread of resistance, first
to chloroquine and followed by resistance to sulfadoxine-pyrimethamine, progress in
malaria control faltered. As demonstrated by the faltering progress of these campaigns
with the emergence of resistance, the availability of effective antimalarials for treatment
is a critical component of malaria control projects. New compounds with antimalarial
properties are necessary both for treatment as well as for the protection of our current
first-line antimalarials, as having multiple first-line treatments limits the selective
pressure on each individual drug.

The antimalarial properties of the artemisinin compound were in a sense
rediscovered in 1971 during an effort by the Chinese government to develop a new
antimalarial, a need that was accentuated by the Vietnam War as well as widespread
chloroquine and sulfadoxine-pyrimethamine resistance in the region (Mita & Tanabe
2012). Artemisinins are derived naturally, although within the last decade, artemisinin
precursors have begun to be synthesized using genetically engineered Saccharomyces
cerevisiae yeast (Ro et al. 2006). Artemisinin compounds are derived primarily from the
Artemisia annua species, although artemisinin derivatives can also be extracted from
other species, including A. Lancea and A. opiacea (Chrubasik & Jacobson 2010).


Within the context of previous antimalarials, artemisinins are not only effective
against malaria but also comparatively safe and well-tolerated. As such, the potential loss
of these drugs to widespread resistance is particularly grave, as no other substitutes could
presently replace them. The artemisinin compound belongs to the chemical class of
sesquiterpene lactone compounds. Artemisinins have a prominent endoperoxide bridge
that is crucial for the compounds’
antimalarial function (O’Brien et al. 2011)
(Fig. 1). A number of artemisinin
derivatives have been produced
synthetically which are used as partner
drugs in ACT. These include
dihydroartemisinin, the reduced
compound; arteether or artemotil, the
ethyl ether form; artemether, the methyl

Figure 1: The artemisinin compound with its endoperoxide
bridge (*), critical for the drug’s activity.

ether form; and artesunate, the
hemisuccinate form (Chrubasik and Jacobson 2010). In the bloodstream, artesunate,
artemether and artemotil are hydrolyzed back into dihydroartemisinin (Dondorp et al.
Regarding the drug’s pharmacokinetic profile, artemisinins are fast-acting with
short half-lives. The half-lives of the drugs are typically between 1 to 3 hours.
Consequently, the drug family is inadequate for prophylaxis. However, artemisinins’ fast
half-lives are believed to reduce the probability of the organism developing resistance,
since exposure to the drug is only for a short period of time (Dondorp et al. 2010). The


efficacy and fast parasite clearance rates of artemisinin derivatives are in part attributable
to the compounds’ effect on the broadest range of asexual stages of malaria of all known
antimalarials, from the ‘ring-form’ to mature trophozoites. The compounds also have
known gametocytocidal activity, inhibiting further malarial transmission (Fairhurst et al.
2012; O’Brien et al. 2011). Additionally, the rate at which new, resistant alleles appear in
artemisinin-treated malaria is lower than the rates for other drugs such as atovaquone or
pyrimethamine as monotherapies (Klein 2013). Artemisinins are also effective in cases of
severe malaria. In one study, artesunate was found to be 35% more effective than quinine
in curing severe cases of malaria (Dondorp et al. 2010). However, artemisinin
monotherapy is not as effective as when used in combination and requires a seven-day
course of treatment to achieve a radical cure. A study found that recrudescence, or
treatment failure of a standard treatment resulting in observable parasitemia levels, occurs
in roughly 11 percent of infections after treatment with seven days artemisinin
monotherapy even without artemisinin resistance (Price et al. 1998). This is largely
explained by the elimination of on average 1012 parasites through seven days of
artemisinin monotherapy. If initial parasitemia levels are above that, then a seven-day
course will not provide a radical cure (Dondorp et al. 2010).
Because of artemisinin’s fast clearance rates and excellent safety profile,
artemisinin-based combination therapy (ACT) has been the WHO recommended
treatment for malaria since 2001 (World Malaria Report 2013). ACTs combine an
artemisinin derivative with a longer-lasting partner drug, making the combination
particularly effective due to the pharmacokinetics of the two components. The
artemisinin derivative is effective in drastically lowering parasitemia levels within the


first three days, equivalent of 1½ of P. falciparum’s 48-hour, erythrocytic lifecycles.
(Mita & Tanabe 2012). In non-resistant populations, a 3-day course of ACT reduces
parasitemia levels by a factor of 108 and after 48 hours of treatment, 95% of patients
show negative blood tests (Anderson et al. 2010). The partner drug is effective in
eliminating remaining parasites, particularly those that are resistant to artemisinin and
those that outlast the activity of the artemisinin derivative within the first three days
(Fairhurst et al. 2012). The WHO currently recommends five forms of ACT: artemether +
lumefantrine, artesunate + mefloquine, artesunate + amodiaquine, artesunate +
sulphadoxine-pyrimethamine, and dihydroartemisinin + piperaquine (DHP) (Table 1).

Table 1: WHO-recommended ACTs, as of 2014.

artemether + lumefantrine (AL)
artesunate + mefloquine (ASMQ)
artesunate + amodiaquine (ASAMQ)
artesunate + sulphadoxine-pyrimethamine (ASSP)
dihydroartemisinin + piperaquine (DHP)

Combination therapies, like those used for treating tuberculosis and HIV, offer
several advantages over monotherapies. ACT provides a faster course of treatment than
artemisinin monotherapy alone: artemisinin monotherapy requires a seven-day course
(Mita & Tanabe 2012), while ACT requires a three-day treatment. Combination therapies
also reduce the probability of developing drug resistance. The probability of resistance to
a combination therapy is the product of the probability of developing resistance to each
component independently, assuming resistance arises by independent and unrelated


mutations. Therefore, since these probabilities are less than 1, the probability of
developing resistance to a combination therapy is smaller than the probabilities of
developing resistance to either of the individual drugs. This is evidenced in the
circumstance that a mutation in a Plasmodium organism confers resistance against one
drug, but the organism dies when exposed to the partner drug, for which the mutation
does not confer resistance. If resistance is established to the artemisinin derivative, the
partner drug becomes more susceptible to the development of resistance and vice versa
(Fairhurst et al. 2012). The combination essentially becomes a monotherapy as one of the
components is no longer effective, and the development of resistance to the partner drugs
becomes significantly more likely. Although useful as a simple model, due to the
pharmacokinetics of ACTs, the two drugs’ activities only overlap for a short period of
time, meaning it is a simplistic representation of the probabilities (Ferreira et al. 2013).
Likewise, the probabilities of the development and spread of resistance to combinations
versus the individual components are further complicated by factors such as the fitness
costs of most resistance mutations—as observed in many instances of drug resistance, in
the absence of the drug, the resistant mutation are less fit than the rest of the population—
and epigenetic gene regulation (Klein 2013).


A clear and standardized metric for assessing the presence of resistance is a
necessary primary step in containment efforts, as differing definitions of resistance
creates confusion and uncoordinated responses. Antimalarial resistance in the past has


been measured as a threshold proportion of patients who failed a standard treatment
within 28 days of treatment initiation. Due to artemisinin’s rapid action, incomplete
clearance a few days after treatment is thought to be indicative of artemisinin resistance
(Wongsrichanalai & Sibley 2013). The current, standardized metric recommended by the
WHO for defining artemisinin resistance is: (1) resistance is suspected when greater than
10% of patients have observable parasitemia levels after 72 hours of standard,
consecutive ACT treatment administered orally, and (2) resistance is confirmed with the
persistence of parasites after 7 days artemisinin monotherapy or recrudescence within 28
or 42 days (Fairhurst et al. 2012; Wongsrichanalai & Sibley 2013; World Health
Organization 2014a).
The metric for defining resistance is important to containment strategy. Different
metrics would affect understandings of the scope and severity of resistance and would
consequently affect containment response. The 72-hour parasitemia metric is debated,
primarily regarding its rigidity and possible inaccuracy in some situations. For one, the
rigid metric of 72 hours will not always identify drug resistance even when delayed
clearances have occurred, as in situations where patients are clinically immune and
experience delayed clearances within the 72-hour threshold. Similarly, the 72-hour cutoff
does not take into consideration initial parasitemia levels, which results in inaccuracy in
determining resistance, as higher parasitemia levels require longer treatment for
clearance. Other factors that have the potential to delay clearance times include
splenectomies, hemoglobinopathies, and reduced levels of immunity (Anderson et al.
2010; World Health Organization 2014a). Furthermore, not enough is known regarding
the activity and kinetics of the specific artemisinin derivatives and their associated


activity. The partner drug also has a role in the reduction of parasitemia within the first
three days, and kinetic characteristics of the partner drug and resistance to the partner
drug would likely obscure the recognition of artemisinin resistance (Fairhurst et al. 2012).
Likewise, reinfection can be misinterpreted as treatment failure without adequate
diagnostics. Finally, counterfeit or substandard medicines or incomplete treatments will
obfuscate the detection of resistance (Mita & Tanabe 2012).
Some authors have suggested that a more accurate approach to determining
resistance would be to measure parasitemia levels every 6 hours and calculate slopes
from the linear portion of clearance curves to determine clearance rates. In this method,
shallower slopes would be indicative of artemisinin resistance (Fairhurst et al. 2012;
Wongsrichanalai & Sibley 2013). The WHO is in the process of developing an Excelbased metric based on the clearance curve for defining resistance. Others have argued
that not only the slope but also the tails of the curve offer important information
regarding parasite resistance. Although these methods are likely a more accurate measure
of resistance, the 72-hour metric has remained the standard due to its simplicity and
relative accuracy. Changing the metric would further obscure the understanding of
resistance from studies that had used the previous metric.
For in vitro testing in malaria, the half maximal inhibitory concentration (IC50),
the concentration required in inhibit 50% of the sample organisms in vitro, is the most
common metric to determine sensitive versus resistant parasites. Previous antimalarials
have shown strong correlations between in vivo and in vitro susceptibility (Anderson et
al. 2010). However in artemisinins, studies have shown no or weak correlation between
resistant IC50s in vitro and treatment failures in vivo, demonstrating the need for a more


accurate in vitro method (Fairhurst et al. 2012). In vivo tests, however, are also further
complicated by reinfection, which can be interpreted as a resistant primary infection.
A molecular marker for artemisinin resistance was discovered in December, 2013.
The Koch 13 (K13) gene has shown strong correlations between in vivo and in vitro
sensitivity. The discovery will likely change resistance metrics in the near future, as K13
mutations show strong correlations with delayed clearance times. K13 assays have the
potential to soon be a method to diagnose artemisinin-resistant malaria (Ariey et al.
Using the previous metrics, resistant malaria has been confirmed in five countries
of the Greater Mekong Subregion (GMS): Thailand, Cambodia, Myanmar, Vietnam, and
Laos. These cases are concentrated most along the northern border between Cambodia
and Myanmar, and along the border between Cambodia and Thailand (Wongsrichanalai
& Sibley 2013). In Suriname, it was also discovered that a greater proportion of patients
failed artemether-lumefantrine treatment after three days, although the presence of
resistance in South America has yet to be confirmed (Wongsrichanalai & Sibley 2013).
Initially, higher rates of recrudescence were observed in Cambodia, followed by in vivo
studies that first reported delayed clearance rates in 2008 along the border between
Thailand and Cambodia (Dondorp et al. 2009). Some samples have shown higher IC50s
and the ability to proliferate in the presence of the drug. This evidence demonstrates the
initial development of complete resistance, or the ability of the parasite to grow and
reproduce in the presence of the drug as opposed to its ability to survive in dormancy
during the drug’s activity (Noedl et al. 2010). Recent research suggests that quiescence,
or dormancy, mechanisms allow for the protection of the early ring-stage malaria from


artemisinin due to artemisinin’s short-term activity (O’Brien et al). During the first 24
hours following treatment with artemisinin, parasitemia levels for artemisinin-resistant
Plasmodium falsiparum are ten times the levels of artemisinin-sensitive (Ferreira et al.
2013). Furthermore, studies have shown that increasing the dose of artemisinin from
4mg/kg to between 6 and 8 mg/kg is ineffective in clearance of parasites (Fairhurst et al.


A number of factors affect the speed at which resistance develops and spreads. A
thorough comprehension of these factors is necessary for focused containment efforts, as
strategies need to address and, when possible, reduce the influence of these factors. These
factors are separated into biological and innate factors versus pharmaceutical and other,
human-caused factors. The following section elaborates on both categories of factors,
focusing on their impact in the GMS.

Mathematically, the emergence of resistant strains of malaria is dependent on two
variables: the rate at which new resistant mutations arise within an individual parasite and
the rate at which those alleles pass to others (Klein 2013). The probability of resistant
mutations arising in Plasmodium is highest in the organism’s human life cycle stages,
where the greatest number of divisions take place. This is because although Plasmodium


requires the mosquito vector in order for meiotic division, it also undergoes a far greater
number of mitotic divisions within the host. (Klein 2013).
The mechanism of resistance affects the speed at which resistance arises. In
resistance mechanisms that have genetics components, aspects of parasite genetics are
crucial to the development of resistance. The nature of how mutations confer resistance
affects the rate at which resistance develops, in which independent mechanisms—each
mutation confers more resistance—develop in general faster than epistatic mechanisms—
multiple mutations are required before any resistance is conferred.
Transmission intensity also has a role in the spread of resistance. As evidenced in
the GMS, resistance arises more easily in low-transmission areas. In areas of low
transmission, there are lower levels of clinical immunity, resulting in higher parasitemia
levels and consequently a greater proportion of symptomatic patients. Because
parasitemia levels are generally higher in symptomatic patients, the probability of finding
resistant parasites is more likely in these patients since there is a higher probability of
developing resistance purely because of a higher number of replications (Klein 2013).
(Klein 2013). Furthermore, especially in rural setting and areas of low healthcare access,
drugs are used almost exclusively in the treatment of symptomatic patients. Mutations
only give rise to drug resistance if the drug is present to create a selective pressure.
Consequently, resistant mutations will generally not occur as frequently in asymptomatic
patients. Immune individuals, however, likely play a significant role in the subsequent
spread of resistant strains, since they often do not seek treatment. Immune individuals act
as reservoirs of Plasmodium, though they are slightly more likely to pass on sensitive
parasites rather than resistant parasites due to generally lower levels of drug use in this


demographic. With drugs such as artemisinins that have gametocytocidal activity,
increased resistance threatens not only decreased treatment efficacies but also increased
As discussed previously, human movement likely plays a larger role in the spread
of resistance than mosquito movement. This was evidenced in pyrimethamine resistance,
which spread from its origin first along roads and trade routes, rather than spreading
outwards concentrically. The spread of resistance along trade routes demonstrates human
movement rather than mosquito movement appears to be the larger factor in resistance
spread, as spread due to mosquito movement would likely move from the origin more or
less concentrically (Klein 2013).
Parasite development also influences the efficacy of the drugs used and
consequently the probability of developing resistance. Artemisinins are most effective on
the late ‘ring-stage’ and early trophozoite stage of the Plasmodium lifecycle.
Artemisinin’s efficacy and quick clearance rates, however, are due to the drug’s target of
a broader range of developmental stages.
As with other instances of antimalarial resistance, mutations conferring
artemisinin resistance have an associated fitness cost (Rosenthal 2013). In the absence of
the drug, these mutations are relatively less fit, and therefore are outcompeted by wildtype (non-mutant) organisms in subsequent generations. The nature and impact of this
fitness cost is unknown, and the severity of it affects organismal population survival and
consequently disease transmission.
Although much progress has been made in finding a molecular marker for
artemisinin resistance, much is still unknown about the mechanism of artemisinin drugs,


themselves. As of 2002, the Plasmodium genome has been completely sequenced
although much is still unknown about the role of particular genes (Wongsrichanalai &
Sibley 2013). Multiple mechanisms of artemisinin action have been proposed, and no
consensus has been reached about their validity. These include: (1) the inhibition of the
protozoa’s natural detoxification of heme, a byproduct of its ingestion of host
hemoglobin; (2) alkylation of the Plasmodium Translationally Controlled Tumor Protein
(TCTP); (3) interference of Plasmodium mitochondrial function; and (4) inhibition of
ATPase6. Studies have shown that artemisinin’s endoperoxide bridge is critical to the
activity of the drug, and that the drug interacts with iron, which was hypothesized to
originate from Fe-protoporphyrin IX, a product of the parasite’s degradation of host
hemoglobin (O’Brien et al. 2011).
Until recently, very little was known about the mechanism of artemisinin
resistance. Before these recent discoveries, a number of hypotheses had been made
concerning the nature of artemisinin resistance. Many looked to the pfmdr1 gene, a gene
with a role in the resistance to multiple antimalarials, among them amodiaquine,
chloroquine, mefloquine, halofantrine and lumefantrine (Price & Nosten 2001,
Wongsrichanalai & Sibley 2013). A number of other candidate genes were likewise
proposed, including Pfserca (sarcoplasmic reticulum calcium ATPase), and Pfcrt
(chloroquine resistance transporter), although no mutations in any of these three genes
showed strong correlations to artemisinin resistance (Dondorp et al. 2010). A study
demonstrated through clonally identical parasites that an estimated 56-58% of variation
in clearance rates is due to parasite inheritance, and that due to the prevalence of slow
clearance times within the population in the location in Cambodia, the resistant allele is


close to fixation within the population (Anderson et al. 2010). Saralamba et al. 2010
proposed that the current delayed clearance times are due to a decreased susceptibility of
early-stage trophozoites (‘ring-stage’) parasites, as opposed to late-stage trophozoites or
schizonts, narrowing the mechanism of resistance to a single stage of the parasite’s
lifecycle (Saralamba et al. 2010). Other, in vitro studies show that dormant (quiescent)
parasites are more resistant to artemisinin, which was proposed to be because of downregulation of hemoglobin degradation (O’Brien et al. 2011). Two subsequent studies
discovered a region on chromosome 13 of Plasmodium that shows a strong association
with delayed clearance times (Cheeseman et al. 2012; Takala-Harrison et al. 2012). This
created a push to find a gene or set of genes responsible for conferring resistance,
resulting in the discovery by Ariey et al. of the K13 gene (a gene on chromosome 13)
(Ariey et al. 2013). Although a gene closely associated with artemisinin resistance has
been discovered, much is still unknown regarding the mechanism of resistance. It is yet to
be discovered how significant a role this gene plays. Epigenetic factors may also play a
role in conferring resistance. In particular, a recent study found increased histone and
transcription factor expression in the resistant strain (Ferreira et al. 2013).
Another major factor affecting drug resistance is the therapeutic efficacy of the
partner drug. Many regions of the GMS have seen resistance to first-line ACT partner
drugs, which both increases treatment failure rates and increases the sensitivity of the
artemisinin derivative to the development of resistance. With combination therapies, it
becomes difficult to determine which drug is responsible for delayed clearance. In the
GMS, piperaquine, lumefantrine, and mefloquine are the major partner drugs. However,
drug efficacy of all three can be tested though in vitro assays, which allows for the


determination of whether delayed clearance is attributable to partner drug resistance
(Wongsrichanalai & Sibley 2013). With combination therapy partner drugs, there is a
tradeoff between longer lasting partner drugs, which offer more clinical benefit but also
higher risk of developing resistance since the organism is exposed to the drug for a longer
period of time (Whitty & Steadke 2005). True failure of ACT has only been found in
areas with suspected resistance to partner drugs: Cambodia with dihydroartemisininpiperaquine, and Thailand and Cambodia with artesunate-mefloquine (World Health
Organization 2014a). However, resistance to partner drugs with the failure of various
ACTs across the GMS (Fig. 2), including mefloquine resistance in Thailand, in which

Figure 2: Treatment failure rates within the GMS and by countries, including artesunate-mefloquine
(ASU+MEF), artesunate-amodiaquine (ASU+AMO), artemether-lumefantrine (AL),
dihydroartemisinin-piperaquine (DHA+PIP), and artemether monotherapy (ART).


increased copy numbers of pfmdr1 were found to be associated with resistance
(Wongsrichanalai & Sibley 2013).

A number of factors surrounding antimalarials and the access to prevention and
treatment can escalate the development or spread of resistant malaria. Drug access,
dosage, pricing, storage, and quality all affect the selection of drug resistant parasites.
Appropriate dosing of ACTs is critical to the maintenance of effective drugs, as
subtherapeutic concentrations of medicine can provide selective pressure but allow the
parasite to survive and proliferate, accelerating the rate that resistance develops. Selective
pressure is highest at drug doses between 20% and 80% of the maximum inhibitory
concentration (Price & Nosten 2001). Different pharmacokinetic profiles in different
demographics leads to inadequate dosing in certain situations. Studies point to the
possibility of inadequate drug concentrations in dosing in pregnant women and children
(Dondorp et al. 2010; Garner 2013). Dosing is often based on a weight per kilogram of
the patient. However, studies have shown that in pregnant women and children, other
factors affect the level of therapeutic dosing besides weight and blood volume, and that
drug disposition, or the absorbance, metabolism and distribution of the drug within the
body, is markedly different in pregnant women (McGready et al. 2012). This discovery
reinforces the need for alternative methods of dosing for these demographics, particularly
for pregnant women.
Access to malaria treatment is crucial to limiting the burden of malaria in endemic
countries. Drug access in regulated by national drug regulatory agencies, which approve


the use of specific drugs for treatment. Drug access is also influenced by market forces
and interconnected with drug pricing. ACTs are comparatively expensive antimalarials,
especially when compared to sulfadoxine-pyrimethamine and chloroquine. If left to the
private sector, the market price of these antimalarials would be unaffordable for many.
One result of unaffordable medicine is the use of drugs at subtherapeutic doses as patients
buy incomplete courses. This is facilitated by the sale of individual pills rather than
complete blister packs, a practice found in under-regulated pharmaceutical markets
(Bring order to unregulated health markets 2012). This phenomenon results in
subtherapeutic dosing and inadequate treatment as well as the increased selection for
resistant parasites as subtherapeutic doses kill only the more sensitive phenotypes
(Chrubasik & Jacobson 2010). However, ACTs themselves also vary in price, with some
more affordable than others. For example, ASAMQ is less expensive than AL, but the
evidence of underlying resistance to amodiaquine in certain regions makes ASAMQ a
less viable therapy (Whitty & Steadke 2005). One potential solution to the obstacle of
cost is to subsidize the cost of antimalarials in order to increase drug access in the aim of
decreasing the selective pressure for a certain drug. However, even with subsidized costs,
increased surveillance is necessary to ensure that these drugs are in fact being used as
needed and are not being resold for profit.
Similarly, loose combinations (as opposed to fixed-dose combinations, in which
the two drugs are formulated in one tablet) allow for inappropriate combination dosing or
administering one drug as a monotherapy as a means of preserving the medicine for
longer, instead of taking the recommended doses in combination. Access to fixed-dose
combinations is still limited within the GMS, particularly artesunate-mefloquine, which is


unavailable as fixed-dose combination (Dondorp et al. 2010). The continued usage of
monotherapies likewise threatens further development of resistance. Monotherapies had
been used in the GMS for three decades before the switch to ACTs as first-line treatment
(O’Brien et al). Although oral artemisinin monotherapies have been banned by all
countries within the GMS, continued access and limited public knowledge regarding
these drugs threaten containment efforts. Monotherapies are still the predominant form of
artemisinins available in many areas of the GMS. According to a study in Cambodia,
78% of sampled artesunate in the private sector was available as monotherapy (Yeung et
al. 2008).
Finally, national drug regulatory agencies are crucial to ensuring that drugs are
being properly produced and stored, ensuring proper dosing as active ingredients can
degrade faster in improper storage conditions, lowering the therapeutic dosing of each
treatment. National drug regulatory agencies are also critical to enforcing anticounterfeiting measures and prosecuting drug counterfeiters. Counterfeit drugs constitute
a major problem in global health, a problem especially prevalent within the GMS
(Nayyar et al. 2012). Counterfeit drugs most commonly are missing the full therapeutic
concentration of the active ingredient, having been cut or replaced by inert or
occasionally toxic substances. One of the greatest obstacles facing containment efforts is
the large-scale distribution of low-quality and counterfeit drugs within the GMS. The
subtherapeutic concentrations of the active ingredient in counterfeit drugs creates a
selective pressure for the development of resistance, as the concentration of the active
compound is not enough result in a radical cure. Counterfeit drugs have risen drastically
in scope within the last couple decades and have quickly become a major problem in


global health. Counterfeit antimalarials within Southeast Asia most frequently are
produced domestically or imported from China (Newton et al. 2008). Several studies
have looked into the prevalence of counterfeit antimalarials (Lon et al. 2006; Nayyar et
al. 2012). Lon et al. (2006) found that 27% of 451 sampled antimalarials failed to pass
high-performance thin-layer chromatography tests, indicating improper or absent
concentrations of the active ingredients. Nayyar et al. (2012) in a review of studies in
Southeast Asia found 35% of an amalgamated 1437 drug samples failed quality tests.
Both studies demonstrate the scope and potential impact of counterfeit drugs on
resistance within the region. Although very little is understood regarding the scope of the
counterfeiting trade and the prevalence of counterfeiting drugs in pharmaceutical
markets, experts agree that counterfeiting is likely a significant factor in the rise of
resistance, as counterfeits with subtherapeutic concentrations of the active ingredient
increase the selective pressure by killing only the most sensitive parasites.


The GMS, a region encompassing Cambodia, Thailand, Vietnam, Myanmar,
Laos, and southern China, has a long history of the development of antimalarial drug
resistance. The concern in the discovery of delayed clearances with artemisinins
discussed above is in the prospect that artemisinin resistance will follow the same course
as chloroquine and other past antimalarials, originating in Southeast Asia and
subsequently spreading across Asia and through Sub-Saharan Africa, where there exists


the greatest potential of mortality from ineffective antimalarials. Chloroquine was in
wide-scale use throughout the late 1940’s and through the 1950’s until chloroquine
resistance was first discovered along the border between Cambodia and Thailand in 1957
and then along the Panama-Colombia border in 1959 (Mita & Tanabe 2012). Studies of
the genetic makeup of the resistant strain originating in the GMS demonstrate that the
strain subsequently spread throughout Southeast Asia and through Sub-Saharan Africa
(Mita & Tanabe 2012). Chloroquine resistance was discovered in sub-Saharan Africa in
the 1980s after which, due to wide-scale chloroquine use, it became the dominant strain
and spread over the continent (Fairhurst et al. 2012). The resistance to chloroquine
reversed much of the progress achieved in malarial projects through the previous
decades, and studies have demonstrated that chloroquine resistance—and the consequent
inefficacy of first-line malaria treatment—was one of the central factors driving malaria
morbidity and mortality in the decades following (Trape et al. 1998).
Chloroquine is not the only example of antimalarial resistance that has originated
in the GMS and subsequently spread. Following chloroquine resistance, sufladoxinepyrimethamine resistance in the 1970’s and mefloquine resistance in the 1990’s both
emerged in the GMS and spread into Sub-Saharan Africa.
There have been a number of proposed reasons as to why the GMS has been the
origin of resistance of multiple antimalarials. Models have demonstrated that resistance
develops more easily in areas of low-transmission, as previously explained. The GMS is
one such area, although with regions of higher transmission (Cui et al. 2012). Secondly,
in the GMS, both P. vivax and P. falciparum are prevalent, meaning diagnosis is more
challenging and inappropriate treatments are more frequent. In such cases, the treatment


of vivax with chloroquine frequently leads to manifestation of falciparum in co-infected
patients (Cui et al. 2012). Treatment and prevention of malaria is further complicated by
the diversity of Anopheles in the GMS, which are highly varied in population
composition, breeding grounds, and feeding preferences (Cui et al. 2012). Ten species of
Anopheles transmit malaria to humans within the GMS, with two species that inhabit the
forest and forest fringe, Anopheles dirus and An. minimus, the predominant vectors in
malarial transmission within the region (Greater Mekong Subregion Malaria Operational
Plan 2014). Resistance has also been fueled by high selective pressure due to high levels
of drug use. This is in part a result of low transmission, resulting in low levels of clinical
immunity and higher proportions of symptomatic patients. Furthermore, high levels of
migration in and out of the region, in large part due to agricultural production and
extractive industries in these areas, increases transmission and exposes more susceptible
populations to malaria (Dondorp et al. 2010). These migrant populations within the GMS
are often relatively poor and working in rural, forested and forest fringe areas, limiting
their healthcare access and increasing their susceptibility to malaria.
Rural areas of the GMS have relatively low levels of healthcare access and
infrastructure, facilitating malarial transmission and the spread of resistant mutations.
Several countries in the GMS, such as Cambodia and Vietnam, lost significant healthcare
infrastructure due to civil wars and internal conflicts. This lack of infrastructure has
factored into populations within the GMS relying on the private sector to obtain
healthcare. Furthermore, pharmaceutical markets in the region have been largely
unregulated, although increased regulation has escalated within the last decade.


Consequently, access to counterfeit drugs, monotherapies, and inappropriate treatments is
high, often resulting in increased selective pressure.
Lastly, it has been proposed that a distinctly different genetic background of the
Plasmodium population in the GMS might be responsible for making the organism
predisposed to developing mutations and consequently more easily developing resistance,
such as a fault in the population’s DNA mismatch repair (Mita and Tanabe 2012).
A framework of the spread of previous antimalarial resistance provides a
foundation for understanding the challenges of containing antimalarial resistance. The
spread of chloroquine resistance from the GMS into Sub-Saharan Africa provides this
framework, although differences in the drugs and in the responses to resistance limit the
applicability of the comparison to some degree. In retrospect, misguided policy likely
played a role in the speed in which chloroquine resistance emerged. In the 1950’s,
medicated salt projects distributed table salts with low chloroquine concentrations
throughout the Thai-Cambodia border. In order to ensure usage, concentrations of
chloroquine were reduced to miniscule levels in order to not affect the taste of the salt,
often as low as 0.33% of volume. Retrospective analysis shows that the three origins in
which chloroquine resistance arose independently were areas in which chloroquine salt
projects had taken place (Payne 1988). Given our current understanding of mechanisms
of resistance, it is likely that these medicated salt projects quickened the emergence of
resistance, as these perpetual low concentrations of chloroquine provided a constant
selective pressure for resistant parasites.
Unlike artemisinins, the activity of chloroquine is well understood. The
compound works as an antimalarial by preventing the detoxification of heme as the


protist degrades host hemoglobin. This inhibition causes a buildup of heme, a toxic
byproduct within the Plasmodium protist, causing the organism to die. Concentrations of
chloroquine within digestive vacuoles are associated with chloroquine efficacy, where
sensitive Plasmodium show higher concentrations of digestive vacuole chloroquine
concentrations than resistant organisms (Mita & Tanabe 2012). Resistance is conferred
through point mutations in the pfcrt and pfmd1 genes. The pfcrt gene encodes for a
transporter protein in the digestive vacuole (Mita & Tanabe 2012). These resistant
mutations cause an efflux of chloroquine out of digestive vacuoles (Mita & Tanabe
2012). As with many instances of drug resistance, a fitness cost is associated with
chloroquine resistance. Resistant organisms are less fit in the absence of the drug as a
selective pressure. This fitness cost is the likely explanation for several studies that found
that chloroquine sensitivity returns to previously resistant parasite populations after
selective pressure of the compound is removed, a phenomenon observed in a variety of
genetic backgrounds, including Sub-Saharan Africa (Laufer et al. 2006; Mang’era et al.
The consequences of chloroquine resistance were detrimental both to the previous
accomplishments in malaria elimination as well as to human livelihood, as resistance
caused a severe increase in malaria-caused morbidity and mortality. Chloroquine
resistance was largely responsible for a period of increasing deaths of children under five
in Sub-Saharan Africa during an era of decreasing child mortality (Dondorp et al. 2010).



As of 2011, the WHO set forth the Global Plan for Artemisinin Resistance
Containment (GPARC). GPARC provides a framework for containment activities in the
GMS, dividing regions of the GMS into three tiers and providing priorities and actions
depending on the tier. The highest priority tier, Tier 1, includes all regions in which
substantial evidence of artemisinin resistance has been found. Tier 2 encompasses regions
bordering Tier 1 areas, as well as regions that see high rates of migrants from Tier 1
areas. Finally, Tier 3 areas are regions that are endemic to falciparum malaria but that do
not fall into Tier 1 or 2 (World Health Organization 2011). Each Tier is associated with
specific recommendations of containment initiatives (Fig. 3). In April 2013, the WHO
initiated the Emergency Response to Artemisinin Resistance (ERAR), a framework to
guide strategies to contain resistance, building on recommendations in the GPARC.

Figure 3: WHO containment recommendations by tier (Global Plan for Artemisinin Resistance

Despite such frameworks, malaria control within the GMS is a complicated field
involving multiple stakeholders, including non-governmental organizations, national


governments, multinational organizations, and the private sector, and often containment
efforts lack coordination and collaboration between involved groups. Malaria control in
the GMS is implemented through each country’s individual national malaria control
program (NMCP). NMCPs in the GMS are coordinated through hierarchies involving
national, regional, and local agencies. Generally, the ministry of health or similar
department provides policy and oversight of all NMCP activities. The Global Fund to
Fight Aids, Malaria, and Tuberculosis is the largest funder of malaria projects in the
GMS, although other funding institutions and donors play significant roles in the funding
of malaria projects. Governments of endemic countries apply for Global Fund grants to
be used to fund containment and control programs. A number of other organizations play
significant roles in malaria control, ranging from public-private partnerships developing
new antimalarials and subsidizing available drugs, to organizations tracking and
prosecuting counterfeit drug producers and providing educational programs surrounding
proper drug usage (Appendix 1). Diagnostics and treatments are procured through Global
Fund grant money, through non-profits working in the region and through the
government’s own funding and distribution.
Despite such efforts by governments and non-profits within the GMS, the
majority of antimalarial treatments are still obtained through the private sector. In
Cambodia, over 70% of patients use the private sector to obtain malaria treatment (WHO
2010). The availability of monotherapies and counterfeit drugs within these largely
unregulated pharmaceutical markets leads to subtherapeutic dosing and accelerated
development of resistance. Furthermore, in rural areas with low levels of healthcare
access, pharmaceutical vendors are often used as substitutes for healthcare providers in


advising proper dosing and treatment, leading often to inaccurate administration
practices, as these vendors are frequently untrained or have conflicting interests.
Resistance containment has begun in all five countries in which resistance has
been confirmed (Table 2).
A coordinated containment effort began between Thailand and Cambodia first in 2009
along the Cambodia-Thai border as a response to increasing evidence of resistant malaria
in the region.

Table 2: Containment strategies in the GMS by country, including non-ACTs atovaquoneproguanil (AP) and primaquine (PQ) (USAID President’s Malaria Initiative 2014)

Last update to
First-line treatment ASMQ;
45mg PQ
with testing
or available
safety data
Number of drug
monitoring sites











(Tier 1


45mg PQ

30mg PQ

30mg PQ





Analysis using the K13 molecular marker illustrated that resistance likely emerged in the
area in 2001, though clinical evidence of resistance was only established in 2006 (Ariey
et al. 2013). The first-line treatment for the area was changed from artesunate-mefloquine
to dihydroartemisinin-piperaquine due to the emergence of mefloquine resistance. This
change occurred in Pailin in 2008 and throughout Cambodia in 2010. Since the initiation
of containment projects in Cambodia, the overall quantity of falciparum infections has

decreased, though the proportion of resistant infections have increased—from 26% in
2008 to 45% in 2010—consistent with epidemiological models (Maude et al. 2009; WHO
2014a). Suspected piperaquine resistance is believed to be a factor in the slowing
progress of containment efforts, and between 2008 and 2013, four provinces in Cambodia
have seen failures of dihydroartemisinin-piperaquine. A November, 2011 consensus
meeting recommended a switch to atovaquone-proguanil under direct observational
therapy (DOT) but atovaquone resistance was found in 2013, caused by a single point
mutation in cytochrome b, and the drug is increasingly less effective (WHO 2014a).
In Thailand, the first-line treatment was a 2-day course of artesunate-mefloquine,
which was changed in a 3-day course in 2008. The change was not as effective as hoped,
as treatment rates were still above 10% in several provinces. The suspected reason for
treatment failure was the presence of mefloquine resistance, compounded by decreased
artesunate sensitivity. In 2012, artemether-lumefantrine was tested in two provinces, but
the study found greater than 10% failure rates. Consequently, the current first-line
treatment remains an unfixed combination of artesunate-mefloquine (WHO 2014a).
Delayed clearances with dihydroartemisinin-piperaquine, the first line treatment
in Vietnam, were first observed in 2009 in two provinces. Containment activities began
in Vietnam in 2011, and containment in Myanmar also began the same year. Resistance
was estimated to have emerged on the Thailand-Myanmar border in 2001 but was not
observed clinically until 2008. Since 2009, resistant malaria has been discovered in 5
areas of southeastern Myanmar and with all three first-line treatments: artemetherlumefantrine, artesunate-mefloquine and dihydroartemisinin-piperaquine. All three are
still largely effective treatments and continue to be the recommended ACTs in the region.


Genetic mapping of K13 mutants in the region is underway in order to better understand
the spread of resistant strains.
In Laos, containment efforts began in 2014. A 2013 trial in Champasack province
found that 22.2% of patients were parasitemic after a 3-day course of artemetherlumefantrine. Artemether-lumefantrine remains therapeutically effective and is currently
the first-line treatment. As with Myanmar, genetic mapping of the K13 genotypes found
in the region is underway in order to better assess resistance range and spread.


No ‘magic bullet’ strategy yet exists for malaria containment and elimination
efforts. Although efficacious antimalarials are fundamental to containment efforts, a
multipronged approach is necessary for progress and multiple facets need to be
considered. Effective malaria control will include adequate and widespread diagnostics,
preventative efforts and vector control, extensive access to effective and affordable
treatment, continued research and development in malaria control, manufacturing
practices and pharmaceutical regulation, and lastly drug efficacy and progress
surveillance. Each aspect is considered in turn, with recommendations given regarding
future containment efforts. Critical to and underlying these six aspects are the issues of
funding and cooperation between stakeholders, which are addressed in the following


Diagnostics are critical tools in the control and elimination of malaria, as proper
diagnosis is necessary for containment efforts and appropriate treatments. Rapid
Diagnostic Tests (RDTs) and blood microscopy are the two available methods of
diagnosing malaria. The two methods offer different advantages. Blood microscopy
requires a heavier initial investment in the laboratory, microscopes, and training of the
technicians. However, past the initial investment, blood microscopy is cheaper than any
RDT, even with more than twenty RDTs currently available. Furthermore, trained
technicians can estimate parasitemia levels of a patient based on the blood slide, while
current RDTs can only determine the presence or absence of malarial antigens. The
efficacy and feasibility of one or the other is dependent on a number of factors and varies
by region and organization. Without prior investment, RDTs are often the more
appropriate means of diagnosis in many of the regions were resistance has cropped up,
which are often rural and lack the necessary infrastructure for blood microscopy.
G6PD deficiency diagnostics are important diagnostics in the application of
primaquine and are therefore important diagnostics in malaria control strategies. The
CareStart G6PD deficiency screening test has been developed but is currently not ready
for application. CareStart would provide a fast and affordable means of testing for G6PD
deficiency in the application of primaquine, effectively mitigating the risk of primaquine
The development of PCR assays that are mobile and able to be done in the field is
a promising area. Particularly with the recent discovery of the K13 molecular marker,


such assays would provide containment projects with a rapid and portable diagnostic test
for resistance, quickening treatments and containment responses.

Developments in malaria prevention are essential for malaria control and
elimination. With malaria transmission, many treatments and preventions of malaria often
go hand in hand, as the reduction of malaria cases is critical to stopping malarial
transmission. In the beginning of the 20th century, Ronald Ross demonstrated
mathematically that reducing Anopheles populations to a threshold was sufficient to
eliminate malaria (Ross 1909). This was later confirmed by Macdonald and has
subsequently been validated through more complex modeling (Macdonald 1952; Mandal
et al. 2011).
Previous methods of prevention, primarily indoor-residual spraying (IRS) and
long-lasting insecticidal nets (LLIN) remain effective given effective insecticides and
have the potential to decrease mosquito populations and lower transmission rates.
However, these preventions are not adequate control methods alone, as they are not
effective treatments against some outdoor-biting species of Anopheles (Cui et al. 2012).
Use of nets and indoor spraying remain as beneficial adjuncts to control and elimination


The development of an effective malaria vaccine would offer a significant
addition to the current arsenal of control methods. Although no vaccine is yet on the
market, several candidate vaccines are close, and if subsequent clinical trials are passed, a
vaccine could be approved as soon as 2015 (Targett et al. 2013). In the meantime,
available preventions need to continue to be employed to prevent malarial transmission.

Adequate and effective treatments remain the core of malaria control and
elimination projects. Which ACT is used as first-line treatment in an area depends on a
number of factors, including availability of treatments and the stability of local
production, the presence of resistance to specific partner drugs, the specific treatment
costs, and the subsidized distribution of drugs chosen by organizations working in the
region. Often, multiple first-line treatments are used within the same area, which has the
potential to decrease the selective pressure on particular drugs.
Treatment strategy is also crucial to effective malaria control, although no
consensus has been reached regarding the strategy’s efficacy and associated speed at
which resistance develops. The WHO has considered a number of strategies regarding
treatment, including mass drug administration (MDA), mass screening and treatment
(MSAT), and focused screening and treatment (FSAT). MDA and MSAT are used more
frequently in foci of resistance and areas of high transmission. However, the WHO
currently does not endorse MDA, as its benefit is still unclear and the probability of
inciting resistance increases with increased drug administration.


The use of primaquine and other 8-aminoquinolines are the only licensed
antimalarials that target the dormant hypnozoite stage of vivax malaria. Primaquine is
also gametocytocidal, reducing malarial transmission. Mass drug administration with
primaquine raises ethical concerns, as the drug causes intravascular hemolysis in patients
who are glucose-6-phosphate dehydogenase (G6PD) deficient. The prevalence of G6PD
deficiency in the GMS is unclear, although conservative estimates range between 10%
and 20% of the population (Cui et al. 2012, Maude et al. 2012). The WHO has
recommended a 15mg dose of primaquine rather than a 45mg dose, as the lower dose is
considered safer and adequately effective, given not much is known in regards to the
prevalence of G6PD deficiency in the Greater Mekong Subregion. The 15mg dose is now
the WHO recommendation as an adjunct to some ACT treatments (Wongsrichanalai &
Sibley 2013). Although not currently employed, modeling demonstrates primaquine
should ideally be administered 8 days after initiation of ACT treatment, since
gametocytemia is highest 8 days after onset (Dondorp et al. 2010). A delayed primaquine
dose would further complicate the logistics of treatment, making it potential less effective
than when coadministered with the ACT. Tafenoquine, an analogue of primaquine
currently in development, is likely just as dangerous to patients with G6PD deficiency.
However, the approval of tafenoquine is promising due to its longer half-life, meaning it
could be administered as a single dose (Wongsrichanalai & Sibley 2013).
Finally, although little research has been done into the efficacy and safety profiles
of triple combinations, they offer an advantage in the decreased susceptibility of each of
the partner drugs to resistance. Triple combinations are first-line treatments in HIV,
tuberculosis, Helicobacter pylori, and multibacillary leprosy (Dondorp et al. 2010).


Preservation of our current arsenal of antimalarials could be prolonged with the
implementation of triple combinations. Since the safety profiles and efficacies of new
combinations are unknown, triple combinations are a potential area of future research, as
new combinations will have to pass clinical trials.

Continued research in malarial treatments and preventions is pivotal to ensuring
effective defenses in the future. Although only beneficial in the long run, a number of
antimalarials are in various stages of clinical development. Once approved, these drugs
will offer alternatives to current first-line treatments and will allow a decrease in the
selective pressure caused by a single drug. The GPARC describes antimalarials currently
in development, with a variety of drugs currently in clinical trials (Appendix 2).
Trial studies combined with the use of mathematical models assess the efficacy of
new treatments and various strategies to containment. Modeling by Maude et al. (2009)
demonstrated that elimination of resistant malaria would only be achieved with
elimination of all malaria cases in the region, as the last remaining malaria cases would
be the most resistant. Mathematical models such as this guide the long-term strategies
recommended by WHO and other multinational organizations.



As of 2007, WHO member states, including the five countries where resistance
has been confirmed, adopted a resolution to ban oral artemisinin monotherapies and
enforce their removal. WHO has also worked with the major producers of oral
artemisinin monotherapies, and since 2005, 56 of the 86 major producers have withdrawn
these drugs from the market (Withdrawal of oral artemisinin monotherapies).
A number of organizations and governments are working in collaboration to
ensure stricter regulation of imported and domestically produced pharmaceuticals, as well
as to prosecute counterfeit drug producers. These include national drug regulatory
agencies, INTERPOL, the WHO International Medical Products Anti-Counterfeiting
Taskforce, U.S. Pharmacopeia, and the Counterfeit Drug Forensic Investigation Network.


Underlying all containment efforts are two areas where immediate acceleration
and progress can be made. These areas are containment project funding and collaboration
between stakeholders. Although malaria funding continues to increase, particularly in the
first decade of the 20th century, total global funding only reaches one quarter of expected
need, and since 2012 global funding levels have peaked. According to the WHO, despite
a $100 million from the Global Fund, a funding gap of approximately $300 to $350
million exists in funding activities in the GMS for the period from 2013 to 2015 (WHO
2014a). Subsidized treatment costs are one result of adequate funding, and although
subsidized treatments have increased treatment coverage and lessened the burden of
malaria in the region, funding gaps result in incomplete coverage and preventable


transmission and mortality. Funding is a critical component of all containment efforts,
and without it, containment projects could lose much of the progress gained in malaria
control. There is a need for financing organizations such as the Global Fund to set aside a
fund of money not dependent on the approval of country proposals. Such a fund could
potentially avoid the sudden removal of funding in critical areas of containment.
Increased collaboration between funders is also a crucial area of needed progress, as areas
designated as Tier I or Tier II need adequate funding across the board for containment
activities. Furthermore, financing institutions such as the Global Fund need to improve
application processes for multi-country proposals, as resistance containment exists
predominantly along country borders (Gueye et al. 2012).
Coordination and collaboration between stakeholders is the other aspect of
containment efforts that could immediately be improved upon through increased sharing
of decision making and surveillance information, increased education provision for local
populations highlighting the necessity of good treatment administration practices, and
increased mobilization of community-level healthcare providers. The malaria field has
seen trends of steadily increasing amounts of collaboration over the past decades. Publicprivate partnerships and organizations such as Open Source Malaria and Medicines for
Malaria Venture have begun to use collaboration in research and development to increase
the number of antimalarials approved and produced. Although collaborative effort has
improved greatly over the past few decades with the founding of partnerships such as the
Asia Pacific Malaria Elimination Network (APMEN) or Roll Back Malaria, more can be
done to integrate different organizations and players in malaria control. The WHO has
increased collaboration and coordination by establishing their central headquarters for


artemisinin resistance in Phnom Penh, coordinating donors such as the Australian
government and the Bill & Melinda Gates Foundation as well as project implementation.
However, not all stakeholders are incorporated into one decision-making process and
increased collaboration promises to lessen the needed funding as resources are used more
efficiently and redundant activities are decreased. The need for increased collaboration is
echoed in multiple reports by multinational organizations as well as by independent
authors (Bharati & Ganguly 2013; Roll Back Malaria 2008; World Health Organization
2011; World Health Organization 2013). Bharati & Ganguly (2013), in discussing the
potential need for a change in policy, emphasize the importance that global malaria
control projects address malaria in the GMS “collectively.” Increased collaboration,
particularly in the form of shared surveillance information, will provide organizations
working in the field with increased information for containment efforts as well as current
and accurate information regarding the presence of resistance in neighboring areas. This
collaboration is especially critical among governments within the GMS, as the foci of
artemisinin resistance are along national borders (Bharati & Ganguly 2013). The use of
mobile phones for the proliferation of information is a prospective tool for increased
collaboration in the future (Meankaew et al. 2010).
Furthermore, integration of all available resources is needed, particularly
resources at the grassroots level, including community health workers. Kamal-Yanni et
al. (2012) reviewed the roles and efficacies of different forms of healthcare providers and
found that community health workers were some of the most effective and cost-efficient
ways of providing diagnostics and treatment for malaria. Community health workers need
to be further incorporated into surveillance and treatment activities, as they offer a low-


cost and quickly trained way of implementing containment strategies. As Bharati &
Ganguly (2013) state, “Community participation, women’s cooperatives as well as
micro-financing by Gramin (rural) banks should be encouraged for sustainable financing
and empowering women for increasing awareness about the disease.”
Lastly, collaborative efforts need to include educational goals, particularly for
populations living in Tier I and II regions. These projects need to incorporate the spread
of information surrounding the dangers posed by counterfeit drugs and monotherapies,
and the importance of completing ACT drug courses, even if symptoms cease. The
spread of knowledge surrounding drug administration practices needs to be through a
culturally-appropriate method, particularly through local partners such as local nonprofits or community health workers. If successful, such programs will likely help to
deter monotherapy use and ensure patient compliance. However, access to ACTs, often
access to subsidized ACTs, is a critical prerequisite for educational efforts, as patients
need a viable substitute for the programs to be effective.


If the goal of containment strategies is ultimately to eradicate artemisinin-resistant
malaria, modeling demonstrates that such a goal will only be reached with the elimination
of all malaria in areas of artemisinin resistance. Consequently, the long-term goal of
resistance elimination and malaria elimination become synonymous goals. Ultimately,
the only difference between malaria control and elimination strategies is the emphasis
placed on eliminating the foci of transmission, as most elements of control strategies


overlap with strategies of elimination. Eradicating resistant malaria will require a
heightened emphasis on tracking and treating the last remaining, resistant parasites. Until
such a goal is within reach, elimination and control activities overlap almost entirely.
Malaria control and elimination are dependent on a multi-pronged and continued
approach, consisting of high levels of access to effective antimalarials, wide usage of
diagnostic tests, preventative nets and indoor-residual spraying, as well as hynozoitocidal
medicines to stem malarial relapses and inhibit the delayed reinitiating of transmission.
Both collaboration and funding can be stepped up immediately, as neither rely on the
discovery of new technologies or medicines, which carry no assurances of when they will
be available.
Artemisinin resistance threatens the progress made in the last decades in malaria
prevention and elimination. The spread of artemisinin resistance into high transmission
areas would entail a much higher morbidity and mortality burden from the disease. For
now, there is no ‘magic bullet’ for malaria elimination. Because our best way forward is
through evidence-based methods, and given the current understanding and with current
technology, the solution to malaria control remains complex and multifaceted.
At least for the near future and until more effective treatments come along, the
world of malaria control seems to be bound to a seemingly inevitable struggle with drug
resistance. As new and effective treatments are discovered and administered, drug
resistance renders current first-line therapies ineffective. With sage usage of drugs and
strategies to minimize the development of resistance, gains can be made in the meantime,
and the fitness costs of mutations allow for the potential for old antimalarials to be used
again in the future, as resistant strains will die out once the drug is no longer


administered. In the long run, malarial control looks promising. With more acute and
precise resistance monitoring information systems and following the general trend of
increased collaboration within the field of malaria control, resistance will be controlled
more effectively, and access to diagnostics and effective treatments will be provided for
more people. However, this optimism is dependent on the continuation of increased
collaboration between groups, economic and political stability within the region, and the
continuation and scaling-up of international funding. Until a magic bullet becomes
available, malaria control will be an integral part of global health efforts. However, as
long as effective treatments remain available and with continued collaboration and
funding, the impact of malaria on human quality of life will continue to diminish.


Appendix 1: Key organizations involved in malaria control and elimination within the GMS (World
Health Organization 2010)

ACTMalaria Foundation
Armed Forces Research Institute of Medical Sciences (AFRIMS)
American Refugee Committee (ARC)
Asian Development Bank (ADB)
Bill & Melinda Gates Foundation (BMGF)
Family Health International (FHI)
Health Unlimited (HU)
Institut Pasteur Cambodia
Institute of Tropical Medicine (ITM), Antwerp, Belgium
International Organization for Migration (IOM)
Japanese International Cooperation Agency (JICA)
Japanese Ministry of Health, Labour and Welfare
Kenan Institute Asia (Kenan)
Mahidol-Oxford-Wellcome-Trust Tropical Medicine Research Unit (MORU)
Malaria Consortium
Malteser International
Management Sciences for Health, Rational Pharmaceutical Management Plus
(MSH/RPM Plus)
M de cins Sans ronti res (MS )
Medicines for Malaria Venture (MMV)
Partners for Development (PFD)
Population Services International (PSI)
Reproductive and Child Health Alliance (RACHA)
Southeast Asian Ministers of Education Organization Tropical Medicine and Public
Health (SEAMEO TROPMED) network
Thailand Ministry of Public Health – U.S. Centers for Disease Control and Prevention
(TUC) collaboration
Three Diseases Fund for HIV/AIDS, TB and Malaria
Tropical Diseases Research (TDR)
University Research Co., LLC (URC)
US Pharmacopeia, Drug Quality and Information (USP DQI)
USAID-Regional Development Mission (RDM)-Asia
U.S. Centers for Disease Control and Prevention (CDC)
WHO Collaborating Centre for Malaria, Schistosomiasis and Filariasis, Chinese Center
for Diseases Control and Prevention (China CDC), Shanghai, China.
WHO Collaborating Centre for Malaria Training and Research, Department of Medical
Research (Lower Myanmar), Ministry of Health, Yangon, Myanmar.
WHO Collaborating Centre for Reference and Research on Biological Characterization of
Malaria Parasites, Chulalongkorn University, Bangkok, Thailand.
WHO Collaborating Centre for Clinical Management of Malaria, Mahidol University,
Bangkok, Thailand

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