Estimated Under-Five Deaths Associated with Poor-Quality Antimalarials in Sub-Saharan Africa

Abstract

Many antimalarials sold in sub-Saharan Africa are poor-quality (falsified, substandard, or degraded), and the burden of disease caused by this problem is inadequately quantified. In this article, we estimate the number of under-five deaths caused by ineffective treatment of malaria, because of consumption of poor-quality antimalarials in 39 sub-Saharan countries. Our estimates were calculated as the product of the number of private sector antimalarials consumed by malaria-positive children in 2013; the proportion of private sector antimalarials consumed that were of poor-quality; and the case fatality rate (CFR) of under-five malaria-positive children who did not receive appropriate treatment in each country and involved uncertainty analysis using the Latin hypercube sampling. An estimated 122,350 (interquartile range [IQR]: 91,577-154,736) under-five malaria deaths were associated with consumption of poor-quality antimalarials, representing 3.75% (IQR: 2.81-4.75%) of all under-five deaths in our sample of 39 countries. There is considerable uncertainty surrounding our results because of gaps in data on case fatality rates and prevalence of poor-quality antimalarials. Our analysis highlights the need for further investigation into the distribution of poor-quality antimalarials and the need for stronger surveillance and regulatory efforts to prevent the sale of poor-quality antimalarials.
© The American Society of Tropical Medicine and Hygiene.

Full text

Am. J. Trop. Med. Hyg., 92(Suppl 6), 2015, pp. 119–126
doi:10.4269/ajtmh.14-0725
Copyright ©2015 by The American Society of Tropical Medicine and Hygiene
Estimated Under-Five Deaths Associated with Poor-Quality Antimalarials
in Sub-Saharan Africa
John P. Renschler, Kelsey M. Walters, Paul N. Newton, and Ramanan Laxminarayan*
Center for Disease Dynamics, Economics and Policy, Washington, District of Columbia; Worldwide Antimalarial Resistance Network,
Centre for Tropical Medicine, Churchill Hospital, University of Oxford, United Kingdom; LOMWRU, Microbiology Laboratory,
Mahosot Hospital, Vientiane, Lao People’s Democratic Republic; Princeton Environmental Institute, Princeton University,
Princeton, New Jersey; Public Health Foundation of India, New Delhi, India
Abstract. Many antimalarials sold in sub-Saharan Africa are poor-quality (falsified, substandard, or degraded), and
the burden of disease caused by this problem is inadequately quantified. In this article, we estimate the number of under-
five deaths caused by ineffective treatment of malaria associated with consumption of poor-quality antimalarials in
39 sub-Saharan countries. Using Latin hypercube sampling our estimates were calculated as the product of the number
of private sector antimalarials consumed by malaria-positive children in 2013; the proportion of private sector anti-
malarials consumed that were of poor-quality; and the case fatality rate (CFR) of under-five malaria-positive children
who did not receive appropriate treatment. An estimated 122,350 (interquartile range [IQR]: 91,577–154,736) under-five
malaria deaths were associated with consumption of poor-quality antimalarials, representing 3.75% (IQR: 2.81–4.75%)
of all under-five deaths in our sample of 39 countries. There is considerable uncertainty surrounding our results because
of gaps in data on case fatality rates and prevalence of poor-quality antimalarials. Our analysis highlights the need for
further investigation into the distribution of poor-quality antimalarials and the need for stronger surveillance and regula-
tory efforts to prevent the sale of poor-quality antimalarials.
INTRODUCTION
Each year malaria causes an estimated 207 million (M)
clinical cases worldwide resulting in an estimated 627,000–
1,238,000 deaths (0.3–0.6% of clinical cases), the majority in
sub-Saharan Africa.
1,2
Children under 5 years of age in this
region have the highest risk of contracting and dying from
malaria.
3
Artemisinin-based combination therapies (ACTs)
are the first-line treatment recommended by the World Health
Organization (WHO) and are vital to reduce the burden of
childhood malaria.
1,4,5
In Africa, the widespread availability of
ACTs through both public and private sectors has lowered
malaria morbidity and mortality rates
1
and reduced the selec-
tion pressure for emergence of drug-resistant parasite strains
caused by monotherapies.
4
Despite the clinical advantage of
ACTs, many non-artemisinin-based monotherapies (includ-
ing chloroquine, quinine, halofantrine, and amodiaquine) are
still widely available throughout the private sector.
6,7
Many antimalarials sold worldwide are poor-quality. Qual-
ity issues span all classes of antimalarial agents including
diverse examples of falsification and substandard production
(Panel).
3,8
Results aggregated from surveys of antimalarial
quality taken between 2001 and 2010 from 21 countries in sub-
Saharan Africa show that 35% of samples (796 of 2,297) failed
chemical analysis.
3
Although many antimalarials purchased
in sub-Saharan Africa are of poor quality, the quality varies
greatly by location.
3,9
ArecentreviewoftheWorldwideAnti-
malarial Resistance Network (WWARN) antimalarial quality
database warned against generalizations, given the frequent use
of inadequate sampling techniques, the need for standardiza-
tion of chemical analysis, and the scarcity of samples com-
pared with the total volume of antimalarials consumed.
10
The
review found no reports of antimalarial quality for 17 of the
44 malaria-endemic sub-Saharan African countries.
10
Factors associated with the production and sale of poor-
quality antimalarials include inaccessibility and high price of
quality ACTs, limited regulatory oversight, lack of penalties,
self-prescribing practices, poor knowledge about product
authenticity, and a large, unregulated private sector for pur-
chasing pharmaceuticals.
5,11,12
The World Health Organiza-
tion (WHO) estimated that 30% of countries lack any
capacity to oversee medicine manufacture, importation, or
distribution.
12
To date, South Africa, Kenya, and Tanzania
are the only malaria-endemic African countries with WHO-
prequalified laboratories for drug quality testing.
10
Understanding the market penetration and consequences
of poor-quality antimalarials is important but challenging for
two reasons. First, many children with malaria are treated in
informal private sectors, making it difficult to monitor all
transactions. Second, many children are given antimalarials
inappropriately when they present with a non-malarial febrile
illness. In 2013, malaria-positive children consumed only 49%
of the estimated 153 M (interquartile range (IQR): 140–167 M)
private sector antimalarial courses purchased in African coun-
tries to treat under-five cases of fever.
13
Disease progression
due to improper (or lack of) diagnosis makes it harder to iden-
tify treatment failures caused by poor-quality antimalarials.
Although the private sector accounts for the majority of
available antimalarial quality data, evidence indicates that drug
quality is a problem in public and nongovernmental organiza-
tion (NGO) sector distribution chains as well.
14
Recently,
falsified artemether–lumefantrine with labels mimicking
those on the Global Fund/Affordable Medicines Facility-
malaria’s (AMFm’s) quality-approved ACTs have been found
to be widely distributed.
15
Consumption of poor-quality antimalarials is associated with
adverse health effects due to untreated malaria or toxic ingre-
dients, accelerated emergence of drug-resistant malaria para-
sites because of subtherapeutic drug levels, and reduced
consumer confidence in medicine, health care providers, and
regulatory agencies.
16–18
To date, there has been limited anal-
ysis of the burden caused by poor-quality antimalarials, and
*Address correspondence to Ramanan Laxminarayan, Center for
Disease Dynamics, Economics and Policy, 1616 P Street NW, Suite
430, Washington, DC 20036. E-mail: ramanan@cddep.org
119

even the order of magnitude of health consequences remains
to be investigated.
We used a simple uncertainty model to estimate the num-
ber of under-five malaria deaths attributable to poor-quality
antimalarials in sub-Saharan Africa in 2013. Our approach
was favored over more complex alternatives because of data
limitations. This exercise is intended to aid researchers and
policymakers by providing an approximate quantification of the
burden of poor-quality antimalarials and guiding the collection
of data needed to refine these estimates.
METHODS
We calculated the number of under-five deaths caused by
Plasmodium falciparum (referred to as malaria) infections
that persist because children consume poor-quality antima-
larials instead of efficacious antimalarials across 39 countries
in sub-Saharan Africa. We performed an uncertainty analy-
ses using Latin hypercube sampling (LHS) (10,000 simula-
tions) described by Blower and others.
19
We performed all
analyses using the R programming language and created an
interactive, publicly available R package that can be used to
perform and visualize our calculations using alternative input
values (S1).
For each country, we calculated the number of under-
five deaths caused by malaria treatment failure because of
consumption of poor-quality antimalarials as the product:
the number of private sector antimalarials consumed by
malaria-positive children in 2013, the proportion of private
sector antimalarials consumed that were poor-quality, and the
case fatality rate (CFR) of under-five malaria-positive chil-
dren who consumed poor-quality antimalarials. We included
all countries for which antimalarial consumption estimates
were available.
13
LHS is an efficient, stratified Monte Carlo sampling design.
Under the LHS scheme, a probability distribution is con-
structed for each input parameter that is not known with
certainty. Supplemental Tables 1–3 describe the distribu-
tions used for the 79 input parameters in our model. These
79 parameters were categorized into the three input types,
described in more detail below.
Prevalence of poor-quality antimalarials. We used avail-
able sample data describing the proportion of ACTs and
sulfadoxine–pyrimethamine (SP) drugs failing chemical test-
ing for nine countries (Cameroon, Ethiopia, Ghana, Kenya,
Madagascar, Nigeria, Senegal, Tanzania, and Uganda) to con-
struct probability distributions for the proportion of private
sector sales that are poor-quality antimalarials.
20,21
For each
of these countries we used a normal approximation of the
sampling distribution of the sample proportion. For the
remaining 30 countries, we constructed a uniform distribution
with a minimum (min) of 0% and a maximum (max) of 40%,
consistent with the range of samples that failed testing
reported in reviews of antimalarial quality surveys (Supple-
mental Table 1).
3,9
Antimalarial drug sales. Cohen and others
13
provided
country-specific estimates of the number of private sector
antimalarial sales for treating under-five malaria-positive chil-
dren in 2013. For the LHS analysis, we constructed normal
distributions for each nation (Supplemental Table 2). The
methods for the sales estimates are described in detail else-
where, but here we provide a brief overview.
13
Household
survey data were used to estimate the annual number of
under-five fevers, the fraction of fevers treated with an anti-
malarial, and the fraction of fevers treated in the private
sector in 2013. These values were multiplied to get the private
sector under-five demand for antimalarials. Next, the fraction
of fevers caused by malaria was calculated as a function of the
P. falciparum parasite rate. This fraction was applied to the
demand estimates to calculate the annual number of under-
five malaria episodes treated with antimalarials purchased in
the private sector.
CFR of under-five malaria episodes treated with poor-quality
antimalarials. We constructed a uniform probability distri-
bution around the mean CFR for under-five malaria cases
used by WHO for constructing mortality estimates for low-
transmission countries in Africa (min CFR of 0.2% and max
CFR of 0.6%).
22
This distribution was applied to all countries
(Supplemental Table 3).
RESULTS
Our uncertainty analysis results provide estimates of
under-five malaria mortality associated with consumption of
poor-quality antimalarials. Table 1 presents the results from
10,000 calculations performed following the LHS scheme
with the probability distributions described in Supplemental
Tables 1–3. The estimated median number of under-five malaria
deaths associated with consumption of poor-quality antimalar-
ials across the 39 countries was 122,350 (IQR: 91,577–154,736).
Nigeria, which had the largest estimated number of antimalarial
sales to under-five malaria-positive children (30,225,237 courses),
as well as the highest prevalence of poor-quality antimalarials
(64%), accounted for a majority of the estimated deaths, with a
median of 74,188 (IQR: 54,931–96,132) (Figures 1 and 2).
13,21
Table 1 and Figure 3 present the number of deaths caused by
poor-quality antimalarials as a percentage of 2010 under-five
malaria death estimates. Figure 4 presents the number of deaths
caused by poor-quality antimalarials as a proportion of 2012
all-cause under-five death estimates (Supplemental Table 5).
Supplemental Table 4 presents the median number of deaths
Panel: definition of poor-quality antimalarials. Our use of the
term antimalarial encompasses all classes of antimalarial agents
(ACTs, non-artemisinin combination therapies, non-artemisinin
monotherapies, artemisinin monotherapies, etc.). We use the
term poor-quality antimalarials to refer to all antimalarials that
are falsified, substandard, or degraded. Falsified antimalarials
carry false representation of identity or source. We do not use
“counterfeit” because of the intellectual property connotations
associated with the term. Substandard antimalarials fail to meet
the specifications outlined by an accepted pharmacopeia or the
manufacturer’s dossier because of factory errors or negligence.
Degraded antimalarials fail to meet the specifications because of
inappropriate storage or expiration. We adopt the same defini-
tions used by the Worldwide Antimalarial Resistance Network
in support of its efforts to standardize terminology and quality of
medicine field surveys.
10,30
These definitions differ slightly from
those proposed by other organizations. The Institute of Medicine
(IOM) also recommends the terms falsified and substandard but
does not consider degraded drugs separate from substandard
drugs.
9
In place of falsified, WHO uses “spurious/falsely-labeled/
falsified/counterfeit” (SFFC) to refer to fraudulently produced
medication.
31
WHO also uses the term substandard, but like
IOM, WHO does not classify degraded drugs separately.
32
120 RENSCHLER AND OTHERS

caused by poor-quality antimalarials alongside 2010 under-five
deaths due to other causes.
DISCUSSION
There are several reasons it is difficult to estimate the health
burden associated with widespread use of poor-quality anti-
malarials in sub-Saharan Africa. These reasons contribute to
the uncertainty of our numerical results.
First, many poor-quality antimalarials are consumed by
malaria-negative individuals. Our analysis attempts to recon-
cile the extensive use of poor-quality antimalarials with the
significant overtreatment of febrile illness as malaria. Since
many malaria-negative patients take antimalarials, improving
febrile illness diagnostics might save more lives than reduc-
ing the prevalence of poor-quality antimalarials. Our analysis
and methodology aim to inform this policy decision by iso-
lating deaths caused by untreated malaria because of con-
sumption of poor-quality antimalarials from deaths caused
by untreated febrile illnesses because of diagnostic failures.
Future research should focus on constructing estimates for
the number of under-five deaths avertable through improved
diagnosis of febrile illnesses.
Another difficulty with calculating the burden of poor-quality
antimalarials is that not all legitimate antimalarials save lives.
Even if poor-quality antimalarials are eliminated, there will
still be excess mortality among children who consume genuine
antimalarials (such as chloroquine) that are ineffective
because of drug resistance. Because the “consequences” of
poor-quality antimalarials depend on the efficacy of the gen-
uine medicines, our estimates represent “the number of
under-five deaths avoidable if children consume ACTs (or an
effective alternative) instead of poor-quality antimalarials,”
as opposed to “the number of under-five deaths avoidable if
poor-quality antimalarials are eliminated.”
A further challenge is accurately selecting a CFR for under-
five malaria episodes that are treated with poor-quality anti-
malarials. This is an important decision, since the imprecision
of our total death estimates is directly tied to the variation in
CFR inputs used across the 10,000 simulations. This process
is complicated because the chemical composition of poor-
quality antimalarials is variable.
8
The major concerns for
Table 1
Estimated under-five deaths caused by poor-quality antimalarials
Country Min First quartile Median Mean Third quartile Max Median as % of malaria deaths*
All countries 38,772 91,577 122,350 125,012 154,736 269,705 22.33
Nigeria 13,220 54,931 74,188 77,231 96,132 206,618 41.96
Uganda 1,589 7,374 10,138 10,811 13,556 31,419 53.45
DRC 1 3,178 6,501 7,399 10,596 32,251 7.99
Ghana 390 3,068 4,223 4,527 5,669 14,439 41.22
Cameroon 309 2,521 3,520 3,756 4,730 12,119 23.18
Burkina Faso 0 1,463 2,991 3,421 4,892 15,146 10.18
Cote
´d’Ivoire 0 1,102 2,277 2,591 3,703 10,317 11.08
Mali 0 998 2,050 2,325 3,332 10,414 10.59
Mozambique 0 738 1,491 1,746 2,484 7,489 6.63
Madagascar 0 886 1,240 1,339 1,695 4,314 46.69
Benin 0 528 1,053 1,207 1,713 5,368 11.76
Niger 0 440 904 1,048 1,507 4,556 6.34
Tanzania 0 596 933 1,038 1,373 4,431 5.99
Malawi 0 379 792 899 1,272 4,317 10.42
Chad 0 326 670 766 1,089 3,198 4.10
Guinea 0 262 547 637 911 2,856 4.19
Sudan 0 268 539 626 901 2,644 11.24
Togo 0 260 523 598 851 2,733 15.27
Sierra Leone 0 241 499 582 829 2,754 5.65
Angola 0 224 464 552 788 2,753 3.83
CAR 0 196 399 460 661 1,860 6.55
Kenya 0 109 215 249 353 1,462 4.53
Liberia 0 84 192 242 344 1,319 6.81
Senegal 0 162 225 238 301 739 6.28
Zambia 0 88 181 215 304 1,072 2.28
Congo 0 40 99 130 187 865 3.00
Burundi 0 43 87 102 148 507 6.42
Gabon 0 21 51 65 92 407 11.26
Rwanda 0 22 46 53 77 248 9.20
Somalia 0 20 43 50 72 234 1.06
Equatorial Guinea 0 4 22 35 52 341 3.57
Zimbabwe 0 6 14 16 23 79 0.60
Guinea-Bissau 0 5 10 13 18 62 0.66
Gambia 0 4 9 11 16 61 0.73
Mauritania 0 3 8 10 14 71 0.94
Namibia 0 1 3 4 6 25 75.00
Swaziland 0 0 0 0 0 0 0.00
Djibouti 0 0 0 0 0 0 0.00
Ethiopia 0 0 0 0 0 0 0.00
CAR =Central African Republic; DRC =Democratic Republic of Congo.
This table displays the results from 10,000 simulations run following the Latin hypercube sampling scheme discussed in the methodology. The values presented depict the estimated number
of under-five malaria deaths caused by treatment with poor-quality antimalarials for 39 sub-Saharan countries. The countries are listed in descending order according to the medians of
10,000 simulations (with the cumulative nation totals in the top row).
*2010 WHO estimates of under-five malaria deaths (Supplemental Table 4).
ESTIMATED UNDER-FIVE DEATHS ASSOCIATED WITH POOR-QUALITY ANTIMALARIALS 121

Figure 1. Estimated annual under-five malaria deaths due to treatment with poor-quality antimalarials. The median (of 10,000 samples)
number of under-five malaria deaths caused by treatment with poor-quality antimalarials (radius) is plotted for 39 sub-Saharan countries for
which antimalarial sales data were available. The y-axis depicts the poor-quality-antimalarial death estimates as a proportion of total 2010 under-
five malaria death estimates made by World Health Organization (WHO) (Supplemental Table 4). The x-axis depicts the fraction of antimalarial
recipients who are treated in the private sector. The color code depicts the proportion of private sector under-five antimalarial demand made by
malaria-positive children. Darker shades reflect higher levels of overtreatment (i.e., febrile disease is presumptively treated as malaria). *Data
were obtained from Cohen and others.
13
Figure 2. Estimated annual under-five malaria deaths due to treatment with poor-quality antimalarials. The median (derived from 10,000 sim-
ulations) number of under-five malaria deaths due to treatment with poor-quality antimalarials is plotted for 39 sub-Saharan countries. The error
bars depict the interquartile range. Nigeria is plotted on a separate scale (Uganda is plotted twice for comparison).
122 RENSCHLER AND OTHERS

Figure 3. Deaths due to treatment with poor-quality antimalarials as proportion of under-five malaria deaths. The median (derived from
10,000 simulations) number of 2013 under-five malaria deaths due to treatment with poor-quality antimalarials is plotted for 39 sub-Saharan
countries as a proportion of 2010 World Health Organization (WHO) under-five malaria death estimates (Supplemental Table 4). The error bars
depict the interquartile range.
Figure 4. Under-five deaths due to treatment with poor-quality antimalarials as proportion of all-cause deaths. The median (derived from
10,000 simulations) number of 2013 under-five malaria deaths due to treatment with poor-quality antimalarials is plotted for 39 sub-Saharan
countries as a proportion of 2012 World Health Organization (WHO) under-five all-cause death estimates (Supplemental Table 5). The error bars
depict the interquartile range.
ESTIMATED UNDER-FIVE DEATHS ASSOCIATED WITH POOR-QUALITY ANTIMALARIALS 123

parameterizing the CFR are the antimalarial potencies of the
poor-quality medicines and the presence of toxic ingredients.
The CFR for a patient treated with a drug that contains toxins
or banned pharmaceuticals exceeds the CFR of untreated
malaria. When poor-quality antimalarials contain subtherapeu-
tic levels of active pharmaceutical ingredients, the CFR should
be lower than the rate of untreated malaria because the drugs
might still prevent deaths due to malaria. When poor-quality
antimalarials have no antimalarial properties and no toxic
activity, the CFR should be identical to untreated malaria.
Selecting a CFR is further complicated by substantial dis-
agreement regarding the CFR for untreated malaria.
23
The
median CFR for untreated under-five malaria from a Delphi
survey of 22 malaria experts was 21.9% (219 deaths in 1,000
cases) for areas with low malaria transmission and 7.8% (78
deaths in 1,000 cases) for areas with high malaria transmission.
23
The CFR range used for our estimates, 0.2–0.6% (2–6 deaths
in 1,000 cases), is based on the 0.45% CFR (4.5 deaths in
1,000 cases) for under-five malaria cases (treated and
untreated lumped together) used by WHO for constructing
their malaria mortality estimates for low-transmission African
countries.
22
The WHO does not document how this 0.45%
CFR is derived, but notes that “case fatality rates from
malaria populations are not well documented ... the case
fatality rates assumed for different countries were assigned
without regard to the availability and utilization of treatment
for malaria, and in practice could vary from the rate used.”
24
The selection of a CFR introduces a large uncertainty into
our modeling framework. When compared with the results
from the Delphi survey, our CFR range reflects a conservative
assumption that poor-quality antimalarials are not entirely
ineffective. This rate was set equal for all 39 countries because
we lacked evidence to make country-specific estimates. With
better data regarding the poor-quality antimalarials, we could
update our estimates to accurately reflect the relative quanti-
ties of toxic, somewhat effective, and inert medication.
Despite the conservative CFR approach, we may be over-
estimating the number of deaths attributable to poor-quality
antimalarials. Five countries had median poor-quality antima-
larial death estimates that accounted for more than 40% of
2010 total under-five malaria-related deaths (Figure 2). Our
uncertainty analysis illustrates the need for more confident
assessments of input parameters and under-five malaria mor-
tality estimates. Here we have used sales data from Cohen and
others,
13
where each “sale” corresponded to one under-five
malaria episode that was treated with at least one antimalarial
purchased in the private sector. Since Cohen and others
13
acknowledged only a binary outcome for treatment-seeking
behavior (whether the child received an antimalarial purchased
in the private sector), the data did not tell us when children
received multiple drugs for a single episode of malaria. In other
words, our model did not support the scenario where a child
who receives a poor-quality antimalarial also receives a quality
antimalarial that can clear the infection. It would be possible
to adjust the survey estimates if we had data describing the
number of antimalarial courses consumed by one child who
presents with a malaria episode in sub-Saharan Africa. This
issue could be avoided if actual retail sales data were avail-
able instead of estimates derived from self-reported surveys.
Furthermore, our analysis was not stratified by severity of
disease. Severity could be an important determinant of the
burden attributable to poor quality antimalarials. We may
be overestimating deaths if severe malaria cases tend to be
treated appropriately with quality drugs while uncomplicated
cases receive poor-quality antimalarials.
Consumer awareness is another factor that complicates
estimates of the burden of poor-quality antimalarials. For our
estimates, we assumed that patients cannot distinguish between
good- and poor-quality antimalarials so that the proportion of
private sector antimalarials that are poor-quality is the same as
the proportion of private sector antimalarials consumed that
are poor quality. However, if consumers are able to avoid
purchasing poor-quality antimalarials, then the prevalence of
poor-quality antimalarials as determined by random samples
would overestimate true consumption patterns.
Another obstacle with constructing death estimates is that
the prevalence of poor-quality antimalarials is still widely
unknown. Where the prevalence of poor-quality antimalarials
is likely to be high, data are inherently scarce. For this reason
we constructed country-specific probability distributions only
for countries with available and reliable data (nine countries
received country-specific probability distributions for the
prevalence of poor-quality antimalarials; Supplemental Table
1). Even then, these reports may not accurately reflect the
status of poor-quality antimalarials, since the samples were
taken from a select number of private outlets and concerned
antimalarials manufactured for all ages, rather than those used
for under 5-year olds. Reports have consistently indicated high
levels of poor-quality antimalarials across sub-Saharan Africa,
but researchers have warned against generalizing the findings
because of high variability.
3,8–10,18
The insufficient sample sizes,
convenience-based sampling designs, narrow sampling focuses
(often examining non-artemisinin derivatives only), and lack of
standardized chemical analysis techniques make it difficult to
accurately estimate the prevalence and burden of poor-quality
antimalarials.
10
Recent projects undertaken by WWARN and
ACTwatch have focused on accurate data collection and
reporting.
25,26
Readers can calculate and visualize alternative
estimates using their own input settings by downloading the R
package we developed for this research (S1).
A further limitation of this study is that our estimates quan-
tify only one aspect of the burden of poor-quality antimalar-
ials, that is, inadequate treatment of children with malaria.
Other consequences include additional health concerns because
of toxic ingredients and the substantial economic costs borne by
families and health-care systems because of untreated malaria.
Moreover, antimalarials that contain subtherapeutic levels of
active ingredients can increase selection for drug-resistant par-
asites.
17
Falsified medicines containing no antimalarial activity
will not on their own engender resistance but will increase the
risk of hyperparasitemia, recrudescence, and gametocytemia;
these conditions could facilitate the spread of resistance.
8,27
The loss of effective antimalarials to resistance is a serious
concern that should be investigated closely.
Despite the previously discussed limitations of our analysis,
this study is a first step toward accurately describing the burden
of poor-quality antimalarials in sub-Saharan Africa. An esti-
mated 122,350 (IQR: 91,577–154,736) under-five deaths were
associated with consumption of poor-quality antimalarials in
39 sub-Saharan African countries in 2013. Although these
results are only approximations, they suggest that poor-quality
antimalarials are important contributors to under-five mortality.
According to our analysis the burden of private sector
poor-quality antimalarials is concentrated in three countries
124 RENSCHLER AND OTHERS

(Nigeria, Uganda, and Democratic Republic of Congo),
which account for 76.7% of all deaths (median estimates)
associated with this problem. Therefore, international efforts
to improve regulation, supply chains, and drug quality testing
could focus on these areas.
Better data are needed both on the market prevalence of
poor-quality antimalarials and on production origin. Chinese
and Indian manufacturers are the most frequently cited
sources of poor-quality antimalarials, but manufacturers in
other countries may be involved as well.
18
International flows
of pharmaceuticals around the world should be tracked, par-
ticularly into sub-Saharan Africa, where the capacity for drug
quality testing and patient protection is least developed.
The falsification of antimalarial pharmaceuticals is a multi-
billion-dollar business that is escalating because some coun-
tries lack appropriate deterrents.
28
This problem requires
investigations, prosecutions, and reductions of profit incen-
tives (achievable by improving access to affordable, quality-
assured antimalarials).
29
Issues of poor quality control can
also be targeted through stricter manufacturing standards
(enforced by medicine regulatory authorities) or support
systems that result in improved factory processes.
29
There-
fore, strengthening institutions in sub-Saharan Africa and in
manufacturing countries such as India and China would be an
effective and potentially cost-effective approach to meeting
global goals for child survival.
Received November 18, 2014. Accepted for publication April 3, 2015.
Published online April 20, 2015.
Note: Supplemental information and tables appear at www.ajtmh.org.
Financial support: This study was supported by grants from the U.S.
Institute of Medicine, the Health Grand Challenges Program at
Princeton University, and the Global Antibiotic Resistance Partner-
ship. The Antimalarial Quality Surveyor of WWARN has been
funded by the French Ministry of Foreign and European Affairs
(FSP Mekong Project), the Bill and Melinda Gates Foundation and
the Wellcome Trust of Great Britain.
Authors’ addresses: John P. Renschler and Kelsey M. Walters, Center
for Disease Dynamics, Economics and Policy, Washington, DC, E-mails:
patrick.renschler@gmail.com and kelseymwalters@gmail.com. Paul
N. Newton, Worldwide Antimalarial Resistance Network, Centre for
Tropical Medicine, Churchill Hospital, University of Oxford, United
Kingdom, and LOMWRU, Microbiology Laboratory, Mahosot Hos-
pital, Vientiane, Lao People’s Democratic Republic, E-mail: paul@
tropmedres.ac. Ramanan Laxminarayan, Center for Disease Dynamics,
Economics and Policy, Washington, DC, Princeton Environmental Insti-
tute, Princeton University, Princeton, NJ, and Public Health Founda-
tion of India, New Delhi, India, E-mail: ramanan@cddep.org.
This is an open-access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the
original author and source are credited.
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126 RENSCHLER AND OTHERS