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Am. J. Trop. Med. Hyg., 93(Suppl 3), 2015, pp. 5–15doi:10.4269/ajtmh.15-0006Copyright © 2015 by The American Society of Tropical Medicine and Hygiene
Malaria Epidemiology and Control within the International Centersof Excellence for Malaria Research
William J. Moss,* Grant Dorsey, Ivo Mueller, Miriam K. Laufer, Donald J. Krogstad, Joseph M. Vinetz, Mitchel Guzman,Angel M. Rosas-Aguirre, Socrates Herrera, Myriam Arevalo-Herrera, Laura Chery, Ashwani Kumar, Pradyumna K.
Mohapatra, Lalitha Ramanathapuram, H. C. Srivastava, Liwang Cui, Guofa Zhou, Daniel M. Parker,Joaniter Nankabirwa, James W. Kazura, and for the International Centers of Excellence for Malaria Research
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Department of Medicine, University ofCalifornia San Francisco, San Francisco, California; Walter and Eliza Hall Institute, Melbourne, Australia; Center for Vaccine Development,
University of Maryland School of Medicine, Baltimore, Maryland; Department of Tropical Medicine and the Center for Infectious Diseases, TulaneUniversity, New Orleans, Louisiana; Department of Medicine, University of California San Diego, La Jolla, California; Alexander von HumboldtInstitute of Tropical Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru; Caucaseco Scientific Research Center, Cali, Colombia; Malaria
Vaccine and Drug Development Center, Cali, Colombia; School of Health, Universidad del Valle, Cali, Colombia; Department of Chemistry,University of Washington, Seattle, Washington; National Institute of Malaria Research-Goa, Panaji, Goa, India; Regional Medical Research
Centre-Northeast, Dibrugarh, Assam, India; Department of Biology, New York University, New York, New York; National Institute of MalariaResearch-Nadiad, Gujarat, India; Department of Entomology, Pennsylvania State University, University Park, Pennsylvania; Program in Public
Health, University of California at Irvine, Irvine, California; Department of Medicine, Makerere University College of Health Sciences,Kampala, Uganda; Center for Global Health and Diseases, Case Western Reserve University, Cleveland, Ohio
Abstract. Understanding the epidemiological features and metrics of malaria in endemic populations is a key com-ponent to monitoring and quantifying the impact of current and past control efforts to inform future ones. The Interna-tional Centers of Excellence for Malaria Research (ICEMR) has the opportunity to evaluate the impact of malariacontrol interventions across endemic regions that differ in the dominant Plasmodium species, mosquito vector species,resistance to antimalarial drugs and human genetic variants thought to confer protection from infection and clinicalmanifestations of plasmodia infection. ICEMR programs are conducting field studies at multiple sites with the aim ofgenerating standardized surveillance data to improve the understanding of malaria transmission and to monitor andevaluate the impact of interventions to inform malaria control and elimination programs. In addition, these epidemio-logical studies provide a vast source of biological samples linked to clinical and environmental “meta-data” to supporttranslational studies of interactions between the parasite, human host, and mosquito vector. Importantly, epidemiologi-cal studies at the ICEMR field sites are integrated with entomological studies, including the measurement of the ento-mological inoculation rate, human biting index, and insecticide resistance, as well as studies of parasite geneticdiversity and antimalarial drug resistance.
INTRODUCTION
Understanding the epidemiological features and metrics ofmalaria in endemic populations is a key component to moni-toring and quantifying the impact of current and past controlefforts to reduce morbidity due to plasmodia infection to alevel that is acceptable from a public health perspective,eliminate malaria by decreasing the reproduction number(R0) to a level at which transmission is not sustained by localmosquito vectors in a defined geographic region, and ulti-mately to eradicate malaria by irrevocably reducing the globalincidence of plasmodia infection to nil.1 Historically, the goalof the Global Malaria Eradication Program (GMEP) initiatedby the World Health Organization (WHO) in 1955 was toeliminate malaria in all endemic areas of the world with theexception of Africa, where the goal was to control malaria.Implementation of the major interventions available at thetime, specifically antimalarial drugs (primarily chloroquine) toreduce infection prevalence in human populations anddichlorodiphenyltrichloroethane (DDT) to shorten mosquitovector viability, resulted in the elimination of Plasmodiumfalciparum and P. vivax transmission in 37 countries wherethese infections were endemic in 1950.2 By the mid-1970s,malaria was eliminated in 27 countries of Europe and North
America.3 The remarkable success of the GMEP in theseareas was aligned with the improvement of the local publichealth infrastructure, the commitment of financial and humanresources that were not realized until after the Second WorldWar, and sustained political commitment. In contrast, in manyother countries where preexisting transmission was high tomoderate, efforts at elimination were largely abandoned bythe late 1960s because of the unanticipated development ofparasite resistance to chloroquine and decreasing efficacy ofDDT against mosquito vectors.The metrics used to monitor and evaluate changes in
malaria transmission at the time varied among, and evenwithin, regions and countries.4 Indicators commonly usedfor surveillance and monitoring included the prevalence ofblood stage infection determined by the microscopic exami-nation of blood smears, the estimated number of deathsattributed to malaria recorded by national or local healthauthorities, and the incidence of clinical malaria. Aside frominfection diagnosed by microscopic inspection of blood smears,the sensitivity and specificity of metrics based on death andclinical manifestations attributable to plasmodia infection wereunclear, particularly, in the many areas where other causesof acute febrile illness and anemia in children were common.Meaningful analyses and comparison of progress toward elimi-nation across different endemic regions with varying malariaepidemiology was compromised given the lack of consensuson the use of a standardized and validated set of metrics.In the wake of the abandonment of the GMEP, the pre-
valence of infection and malaria-related deaths increased in
*Address correspondence to William J. Moss, Department ofEpidemiology, Bloomberg School of Public Health, Johns HopkinsUniversity, 615 North Wolfe Street, Baltimore, MD 21205. E-mail:[email protected]
5
Africa and other areas where transmission was sustained.Because of the increasing number of children and pregnantwomen in Africa who experienced malaria morbidity anddeath during the past decades of the twentieth century, theWHO created the Roll Back Malaria program.5 Launched in1998, the program was based primarily on the deployment ofartemisinin combination therapy (ACT), distribution of insec-ticide-treated bed nets (ITNs) and to a lesser extent, indoorresidual spraying (IRS) of insecticide.6 More recently, thechanging epidemiology of P. falciparum malaria in Africa wasassessed from 2000 to 2010, the time period over which theseinterventions were implemented.7 Using published and publi-cally available data from throughout the region, spatial andtemporal trends of P. falciparum infection were analyzedamong 2- to 10-year-old children (PRPf2–10) as an indicator oftransmission. Downward trends in P. falciparum transmissionwere noted in many areas. However, a major conclusion ofthis comprehensive analysis was that 57% of African residentscontinued to live in areas where transmission was moderate tohigh in 2010.What do these not-so-recent and recent reports of malaria
epidemiology mean in the context of the National Institutesof Health International Centers of Excellence for MalariaResearch (ICEMR) effort, now in the fourth year since itsinception? The ICEMR program was created in a new erawith a goal that goes beyond malaria “control,” an era inwhich eradication has been put back on the table as anachievable goal that might benefit the generation of childrenborn in endemic areas today.8 Knowledge of the cell biology,genetics, genomics, and biochemistry of the parasite, particu-larly in the case of P. falciparum but less in P. vivax (the othermajor Plasmodium species important to human health), hasadvanced remarkably over the past several decades. Equallyimportant, point-of-care diagnostic tests for blood stage infec-tion (i.e., rapid diagnostic tests [RDTs]) and highly sensitivepolymerase chain reaction assays that detect low-densityblood stage infections that may sustain transmission of infec-tion from humans to mosquitos9 are widely used. In addition,antimalarial regimens such as ACTs and wide deployment ofITNs appear to have reduced morbidity and allowed signifi-cant progress toward elimination in low transmission settingssuch as the Solomon Islands and Vanuatu.10 The ICEMR pro-gram thus has the opportunity to evaluate the impact of theseand future interventions across endemic regions, which differin the dominant Plasmodium species, mosquito vector species,resistance to antimalarial drugs, and human genetic variantsthought to confer protection from infection and clinical mani-festations of malaria. These evaluations can be conducted ingreater depth than routinely done by national malaria controlprograms, including detailed molecular analyses of parasitesand vectors and more sophisticated spatial analyses, albeit inmore limited geographical areas.There now exist not only historically used metrics to moni-
tor and evaluate the impact of interventions to control andeliminate malaria, such as infection and malaria attributabledisease prevalence and deaths, but also highly sensitivemolecular and genetic tools that reflect subtle changes in theepidemiology and transmission dynamics of P. falciparumand P. vivax (Table 1). For example, the impact of key inter-ventions such as population coverage with (ITNs), IRS, andcase management can be mapped and tracked using newermetrics such as the force of infection11 (the number of new
infections per person per unit time as determined by molecu-lar genotyping to quantify exposure to new Plasmodiumclones over time) and seroconversion rate (calculated byfitting a reverse catalytic model to age-specific prevalence ofantibody responses to a single or defined set of recombinantmalaria proteins expressed by various stage of the parasitelifecycle). The following sections describe how the ICEMRprogram represents a unique opportunity to compare thevalidity and utility of these and other newly developed met-rics of transmission intensity and clinically relevant indicatorsthat can be used in a standardized manner across the majormalaria-endemic areas of the world to evaluate and guidemalaria control and elimination strategies.
ICEMR FIELD STUDIES OF MALARIASURVEILLANCE, MONITORING, AND EVALUATION
Given the diverse and evolving nature of malaria transmis-sion and its clinical manifestations, it is critical to generatebasic epidemiological information across a range of settings.The ICEMR programs are uniquely positioned to capturethis shifting epidemiology in real time across the globe. AllICEMR programs are conducting field studies at multiplesites with the aim of generating surveillance data to improveunderstanding of malaria transmission and to monitor andevaluate the impact of interventions to inform malaria con-trol and elimination programs. In addition, these epidemio-logical studies provide a vast source of biological sampleslinked to clinical and environmental “meta-data” to supporttranslational studies of interactions between the parasite,human host, and mosquito vector. The basic types of epide-miological studies being conducted by the ICEMR programsare described, with a focus on methodological issues, typesof malaria indicators generated, and the strengths and weak-ness of each study design (Table 2).Health facility-based surveillance. ICEMR field activities
can be divided into four general categories: health facility-based surveillance, cohort studies, cross-sectional surveys,and entomological surveys. Health facility-based surveillanceprovides an efficient means of collecting basic epidemiologi-cal data on large numbers of patients presenting to healthcenters. These data are generally part of a country’s routinehealth management information systems and are one of themain sources of data reported to the WHO and Roll BackMalaria.12 Data collected from health facility-based surveil-lance include the number of symptomatic patients withsuspected malaria, numbers of cases receiving a diagnostictest, the number of confirmed malaria cases, and the numberof malaria deaths. Indicators used include the test positivityrate (the proportion of patients with suspected malaria whoare tested for infection and test positive), malaria case inci-dence (i.e., confirmed malaria cases per 1,000 persons peryear), and malaria mortality rate (inpatient malaria deathsper 100,000 persons per year). The primary advantage ofhealth facility-based surveillance data is the relative ease ofcollecting longitudinal data on a large number of patients atdifferent spatial scales, up to the national level. The primarydisadvantages of health facility-based data is that it is oftenincomplete and of poor quality, limited by variation inhealth-seeking behaviors, and fails to capture asymptomaticand subpatent infections. Many patients may not present tothe formal health-care system and even when they do,
6 MOSS AND OTHERS
TABLE1
Summaryof
keyindicators
used
formalaria
mon
itoringan
devalua
tionan
dsurveilla
nce
Categ
ory
Indicators
Definitions
Primarysource
ofda
ta
Key
controlinterventions
ITN
cove
rage
Propo
rtionof
househ
olds
withat
leaston
eIT
NHou
seho
ldsurvey
sPropo
rtionof
househ
olds
withat
leaston
eIT
Nforev
erytw
ope
ople
Propo
rtionof
prop
ortion
ofindividu
alsrepo
rtingIT
Nusein
previous
nigh
tIR
Scove
rage
Propo
rtionof
househ
olds
spraye
dwithIR
Swith
inthelast
12mon
ths
Propo
rtionof
popu
lation
protectedby
IRSwithinthelast
12mon
ths
Caseman
agem
ent
Propo
rtionof
suspectedmalaria
casesthat
receiveapa
rasitologicaltest
Propo
rtionof
confirmed
malaria
casesthat
receivefirst-lin
etherap
yIPTpcove
rage
Propo
rtionof
wom
enwho
received
atleastthreeor
moredo
sesof
IPTpdu
ring
last
preg
nancy
Categ
ory
Indicators
Definitions
Com
men
tsPrimarysource
ofda
ta
Measuresof
tran
smission
intensity
EIR
Num
berof
infectious
bitesreceived
perpe
rson
per
unittime
Widelyconsidered
gold
stan
dard
measure
oftran
smission
Entom
olog
ysurveys
Infreq
uently
mea
sured
Que
stions
abou
tprecisionan
daccuracy
Parasiterate
Propo
rtionof
popu
lation
foun
dto
carryasexua
lpa
rasites
Reflectionof
intensityof
tran
smission
,im
mun
ity,
andeffectiven
essof
treatm
ent
Cross-section
alsurveys
Dep
ende
nton
agean
ddiagno
stic
metho
dForce
ofinfection
Num
berof
new
infections
perpe
rson
perun
ittime
Difficultto
accurately
measure
incide
ntev
ents
Coh
ortstud
ies
Molecular
techniqu
esha
vebe
enprop
osed
asameans
ofqu
antifyingne
wpa
rasite
clon
esacqu
ired
Seroprevalen
cePropo
rtionof
popu
lation
foun
dto
have
apo
sitive
antibo
dyrespon
seto
aspecific
antige
n(s)
Havebe
encorrelated
withEIR
Cross-section
alsurveys
Can
prov
ide“sna
pshot”of
historical
chan
ges
Onlyalim
itednu
mbe
rof
antig
ensha
vebe
enev
alua
ted
Lackof
stan
dardizationin
metho
dsused
tocolle
ctan
dan
alyzeda
taSe
roconv
ersion
rate
Num
berof
new
seroconv
ersion
spe
rpe
rson
per
unittime.
Calculatedby
fittingareversecatalytic
mod
elto
age-specific
seroprevalen
ceClin
ically
releva
ntindicators
Testpo
sitivity
rate
Propo
rtionof
patien
tswithsuspectedmalaria
who
are
tested
forinfectionan
dtest
positive
Efficient
source
oflong
itud
inal
data
Healthfacility-ba
sed
surveilla
nce
Dep
ende
nton
agean
ddiagno
stic
metho
dsMalaria
incide
nce
Num
berof
confirmed
malaria
casespe
rpe
rson
time
ofob
servation
Influ
encedby
case
detectionmetho
dsCoh
ortstud
iesor
nation
alsurveilla
ncesystem
sCha
lleng
ingto
accurately
measure
Subjectto
misclassification
Dep
ende
nton
agean
ddiagno
stic
metho
dsPreva
lenceof
anem
iaPropo
rtionof
popu
lation
withhe
mog
lobinleve
lbe
low
variou
sthresholds
Efficient
means
ofestimatingbu
rden
ofdisease
Cross-section
alsurveys
Multifactorialc
ausesof
anem
ialim
itsuse
Dep
ende
nton
age
Allcauseun
der
5mortalityrate
Proba
bility(exp
ressed
asarate
per1,00
0liv
ebirths)
ofachild
born
inaspecifiedye
ardy
ingbe
fore
reaching
theag
eof
five
May
beuseful
formon
itoring
tempo
raltren
dsNationa
lsurveilla
ncesystem
sLim
ited
byge
nerallackof
inform
ationon
causes
ofde
ath
Malaria
case
fatalityrate
Propo
rtionof
malaria
casesthat
resultin
death
Gen
erally
limited
toinpa
tien
tsetting/severe
disease
Healthfacility-ba
sed
surveilla
nce
Influ
encedby
source
popu
latio
nan
dqu
alityof
care
Death
may
bemultifactorial
EIR
=en
tomolog
ical
inoculationrate;IPTp=interm
ittent
prev
entive
trea
tmen
tin
preg
nancy;
IRS=indo
orresidu
alspraying
;ITN
=insecticide-treatedbe
dne
t.
7ICEMR MALARIA EPIDEMIOLOGYAND CONTROL
TABLE2
Description
ofon
goingor
plan
nedat
ICEMR
fieldactivities
ofmalaria
surveilla
nce,
mon
itoring
,and
evalua
tion
ICMER
region
alcenters
Field
activities
Hea
lthfacility-ba
sedsurveilla
nce
Coh
ortstud
ies
Cross-section
alsurvey
sEntom
olog
ysurvey
s
Malaw
i*2district
hospitals
(outpa
tientsan
dinpa
tien
ts)
1high
tran
smission
site
3sites
Samples
colle
cted
from
cross-sectiona
lsurveys,
case–con
trol
stud
yan
den
vironm
entalsurvey
s1urba
nhe
alth
center
(outpa
tients)
Age
s1–
50years
300ho
useh
olds
persite
CDC
light
trap
s,ho
useh
oldaspiration
,larvalcolle
ctions
1referral
hospital
(inp
atients)
200pa
rticipan
tsTwiceaye
arActivefollo
wup
everymon
th–
WestAfrica
4commun
ityhe
alth
centers
(outpa
tients)
4sites(3
rural,1urba
n)4sites
4sites
Allag
esEmbe
dded
inthe
coho
rtstud
ies
2weeks
before
cross-sectiona
lsurveysan
dmidseason
700–1,500pa
rticipan
tspe
rsite
Twiceaye
ar(beginning
anden
dof
tran
smission
season
)
30ho
uses
persite
PCD
andactiv
efollo
w-up
everymon
thHLC,P
SC
Southe
rnAfrica
68he
alth
centers(outpa
tien
ts)
3ruralsites
3sites
3sites
Allag
es150ho
useh
olds
persite
Mon
thly
colle
ctions
430pa
rticipan
tsEve
ryothe
rmon
th17
5ho
useh
olds
persite
Activefollo
w-upevery
2mon
ths
CDC
light
trap
s,PSC
,larvalcolle
ctions
EastAfrica
24he
alth
centers(outpa
tien
ts)
3sites(2
rural,1pe
ri-urban
)3sites
3sites
6district
hospitals
(inp
atients;child
renon
ly)
Age
s0.5–10
yearsan
d1ad
ult
perho
use
200ho
useh
olds
persite
Mon
thly
colle
ctions
100ho
useh
olds
persite
Onceaye
ar10
0ho
uses
persite
PCD
andactiv
efollo
w-up
every3mon
ths
CDC
light
trap
s(all);H
LC,P
SC/exittrap
s(sub
set)
Amazon
ia2he
alth
centers(outpa
tien
ts)
2sites
Tobe
design
ed6sites
Age
s≥3ye
ars
HLC,S
hann
ontrap
,screenba
rriers,C
DC
light
trap
s2,000pa
rticipan
tsMon
thly
colle
ctions
(rainy
season
)/bimon
thly
(dry
season
)Activefollo
w-upeverymon
thLatin
America
4ou
tpatient
clinics
4sites
5sites
8siteswithrepe
ated
colle
ctions
(8ho
uses
persite)
3ho
spitals(inp
atients)
Allag
es25
0–460ho
useh
olds
persite
57siteswithsing
lecolle
ction(274
houses)
1,750pa
rticipan
tsCDC
light
trap
s,HLC,P
SC,larvalcolle
ctions
Activefollo
w-upevery6mon
ths
SouthAsia
2statean
d1district
referral
hospitals
(outpa
tientsan
dinpa
tien
ts)
Tobe
design
edTobe
design
ed4sites
6ruralc
linics(outpa
tien
ts)
Weeklycolle
ctions
CDC
light
trap
sIndia*
3ou
tpatient
clinic
sites
2sites
3sites
2sites
Age
s1–70
years
200–300pa
rticipan
tspe
rsite
Mon
thly
colle
ctions
200–300pa
rticipan
tspe
rsite
Twoor
threetimes
aye
ar5–20
houses;5
–18cattle
shed
sde
pend
ingon
site
Activefollo
w-upevery3mon
ths
andfortnigh
tlyfeversurveilla
nce
Aspirationan
dPSC
;larvalcatche
s
Southe
astAsia
86ou
tpatient
clinics/ho
spitals
12sites
12sites
3sites
Allag
es∼150ho
useh
olds
persite
Collections
twiceamon
thTotal
of∼5,400pa
rticipan
ts3–4times
aye
ar30–60ho
uses
persite
Weeklyho
useh
oldvisits
Light
trap
sSo
uthw
estern
Pacific
5clinic
sites(outpa
tien
ts)
3sites
3sites
5sites
Age
s0.5–12
years
2,500pa
rticipan
tspe
rsite
Lan
ding
catchan
dba
rrierscreen
metho
ds45
0–800pa
rticipan
tspe
rsite
Onceaye
arActivefollo
wup
everymon
thCDC
=Cen
ters
forDisea
seCon
trol
andPreve
ntion;
HLC
=hu
man
land
ingcatche
s;IC
EMR
=Internationa
lCen
ters
ofExcellenceforMalaria
Research;
PCD
=pa
ssivecase
detection;
PSC
=py
rethrum
spraycatche
s.*M
iscella
neou
sworkinclud
escase–con
trol
stud
yof
urba
nmalaria
(Malaw
i),rea
ctivecase
detection(Ind
ia).
8 MOSS AND OTHERS
diagnostic testing for malaria is often not performed or is inac-curate. Indeed, malaria case detection rates captured throughhealth facility-based surveillance systems are lowest in coun-tries with the highest estimated burden of malaria.12 Cautionshould be taken in the interpretation of temporal trends inmalaria metrics derived from health facility-based surveillancedue to changes in health-seeking behavior; case definitions; theutilization, methods (i.e., microscopy versus RDT), availabilityand quality of laboratory diagnostic testing used; and the ratesand accuracy of reporting. All of the ICEMR programs areconducting health facility-based surveillance at a range of out-patient and inpatient facilities, usually in collaboration withlocal governments. Advantages to some of these ICEMR-affiliated facilities are that additional resources are beingapplied to improve the quality and timeliness of data throughstandardized approaches to diagnostic testing, quality controlmeasures, reliance on laboratory confirmed cases, and the useof electronic records and short message service text messages.Cohort studies. Cohort studies are generally considered
the gold standard for estimating the burden of malaria in adefined population. These studies involve following a groupof study participants (ideally representative of the targetpopulation of interest) over time with a combination ofactive and passive surveillance activities to measure a varietyof malaria indicators. Common indicators include malariaincidence, period prevalence of parasitemia and anemia, andforce of infection (definitions provided in Table 1). The pri-mary advantages of cohort studies are the high quality andbreadth of data that can be generated. A well-conductedcohort study has the ability to accurately capture all malariacases (both clinical and subclinical) and person-time at risk,necessary requirements for estimating incidence measuresand temporal changes. Cohort studies can be used to esti-mate the impact of population level interventions and are arich source of biological samples linked to a variety of other“meta-data.” The primary disadvantages of cohort studiesare they are expensive and logistically challenging to con-duct. In addition, data from cohorts may not be generalizabledue to their sampling frame, changes in the composition ofthe cohort over time, and the fact that the cohort study itselfmay influence outcomes (for example, the need to treat allparticipants diagnosed with malaria and improved access tomedical care). In low transmission settings, the incidence ofmalaria may be too low to justify the use of a cohort studydesign. Historically, many high-quality cohort studies, such asthe Garki Project,13 were conducted in high transmission set-tings with fewer focusing on malaria across a range of epide-miological settings. The ICEMR programs are addressing thisgap by conducting cohort studies over extended periods innumerous sites around the globe. These studies should pro-vide a wealth of contemporary descriptive data, which will bestrengthened by efforts to standardize methodologies andmetrics, combine datasets, share biological samples for transla-tional studies, and develop novel interactive data managementtools for exploring these rich and complex datasets.Cross-sectional surveys. Cross-sectional surveys provide
another common source of data used for malaria surveil-lance and monitoring and evaluation. Cross-sectional surveysgenerally involve administration of a questionnaire and thecollection of blood samples from members of householdsselected using probability sampling. Common indicators gen-erated from cross-sectional surveys include coverage levels
of preventive interventions (ITNs and IRS), fever case man-agement practices, health-seeking behaviors, health status(under five mortality rate and anemia), and parasite preva-lence for clinical and subclinical malaria (definitions pro-vided in Table 1). Examples of national cross-sectionalsurveys include Demographic Health Surveys and MalariaIndicator Surveys. These data are commonly used by theWHO and Roll Back Malaria as well for malaria risk map-ping, such as that done by the Malaria Atlas Project.14
Advantages of cross-sectional surveys are they are relativelyeasy to do, provide a large amount of information, and aregenerally representative of the population. However, theyare relatively expensive and not performed frequently. Dis-advantages of cross-sectional surveys include limited abilityto capture data on malaria morbidity and monitor trendsover shorter periods or on a fine spatial scale. All of theICEMR programs are conducting cross-sectional surveys.Most of these surveys are being conducted repeatedly indefined geographic areas where other field activities are beingcarried out concurrently, such as entomological surveys. Theseapproaches should improve our understanding of the relation-ships between indicators derived from different study designsand estimate the impact of changes in the coverage levels ofcontrol interventions with clinically relevant indicators mea-sured longitudinally.Entomological surveys. Entomological surveys comprise a
broad range of methodologies aimed at generating data onthe mosquito vector and its interaction with the human host.Methods commonly used to collect mosquitoes include humanlanding catches, Centers for Disease Control and Preventionlight traps, pyrethrum spray catches, exit traps, household aspi-ration, screen barriers, and Shannon traps. Collection methodsare based on the resting and biting behaviors of differentAnopheles species. Once mosquitoes are collected, a variety ofmethods can be used for species identification, identifyingsources of blood meals, and determining if the mosquito isinfected with various stages of the malaria parasite. Commonlyused indicators of transmission intensity include the human bit-ing rate, the sporozoite rate, and the entomological inoculationrate (EIR). The advantages of entomological surveys are theycan provide a rich source of data and the only direct measuresof transmission. The primary disadvantage of entomologicalsurveys is the lack of standardization in methods used to col-lect and interpret data, as well as the limitations of collectionmethods to capture mosquitoes feeding outdoors or during theday. Estimates of indicators derived from entomological sur-veys may be limited by precision and accuracy and lack theability to discriminate small-scale spatial or temporal variabil-ity. This is especially true in low transmission settings where itmay not be possible to collect sufficient numbers of mosqui-toes or detect sporozoites. Entomology surveys are generallynot done outside of the research setting due to logistical chal-lenges and the need for specialized equipment, training, andexpertise. All of the ICEMR programs are conducting somevariation of entomological surveys. The methods used varywidely, largely because of differences in the local environ-ments, characteristics of predominant vectors, and prior experi-ence. Efforts are ongoing to standardize protocols, reagents,and analytical methods across the ICEMR programs. Informa-tion gained from these entomological surveys will fill a knowl-edge gap and improve the quality of these data so critical toimprove our understanding of malaria transmission dynamics.
9ICEMR MALARIA EPIDEMIOLOGYAND CONTROL
TABLE3
Key
malaria
metrics
atIC
EMR
fieldsites
ICMER
Cou
ntry
Site
Predo
minan
tpa
rasites
Predo
minan
tve
ctors
Season
EIR
Parasiteprev
alen
ceIT
Ncove
rage
(%)
IRScove
rage
(%)
Africa
EastAfrica
Uga
nda
Jinja
Plasm
odium
falciparum
Ano
pheles
arab
iensis
Peren
nial
316
%(2–10ye
ars)
583
Ano
pheles
gambiae
s.s.
Uga
nda
Kan
ungu
P.falciparum
An.
gambiae
s.s.
Peren
nial
3018
%(2–10ye
ars)
510
Uga
nda
Tororo
P.falciparum
An.
gambiae
s.s.
Peren
nial
310
60%
(2–10ye
ars)
790
Malaw
iMalaw
iBlantyre
P.falciparum
Ano
pheles
funestus
Sing
leNA
9%(allag
es)
842
An.
arab
iensis
Malaw
iThy
olo
P.falciparum
An.
funestus
Sing
leNA
14%
(allag
es)
850
An.
arab
iensis
Malaw
iChikw
awa
P.falciparum
An.
funestus
Peren
nial
100
30%
(allag
es)
9373
An.
arab
iensis
An.
gambiae
s.s
Southe
rnAfrica
Zam
bia
Nchelen
geP.
falciparum
An.
funestus
Peren
nial
140
50%
(allag
es)
6228
An.
gambiae
Zam
bia
Cho
ma
P.falciparum
An.
arab
iensis
Sing
le<1
1%(allag
es)
830
Zim
babw
eMutasa
P.falciparum
An.
funestus
Sing
le10
10%
(allag
es)
5957
An.
gambiae
WestAfrica
Gam
bia
Gam
bissara
P.falciparum
An.
arab
iensis
Sing
le25
8%(allag
es)
8595
An.
gambiae
Sene
gal
Thiès
P.falciparum
An.
funestus
Sing
le1
1%(allag
es)
200
An.
arab
iensis
An.
gambiae
Mali
Dan
gassa
P.falciparum
An.
gambiae
Sing
le50
48%
(allag
es)
300
An.
arab
iensis
An.
funestus
Mali
Dioro
P.falciparum
An.
gambiae
Sing
le5
24%
(allag
es)
95%
0An.
arab
iensis
An.
funestus SouthAmerica
Amazon
iaPeru
Loreto
Plasm
odium
viva
xAno
pheles
darlingi
Peren
nial
59%
(allag
es)
7055
P.falciparum
Latin
America
Colom
bia
Tierralta
P.viva
xAno
pheles
nuneztov
ari
Peren
nial
36%
(allag
es)
880
P.falciparum
An.
darling
Ano
pheles
albiman
usColom
bia
Bue
naventura
P.viva
xAn.
nuneztov
ari
Peren
nial
<1
5%(allag
es)
950
P.falciparum
Ano
pheles
pseudo
punctip
ennis
An.
albiman
usColom
bia
Tum
aco
P.vivax
An.
albiman
usPeren
nial
36%
(allag
es)
970
P.falciparum
An.
calderon
iPeru
Sulla
naP.
viva
xAn.
albiman
usSing
le<1
1%(allag
es)
4480
P.falciparum
Asiaan
dSo
uthPacific
India
India
Che
nnai
P.viva
xAn.
stephensi
Peren
nial
NA
5.7%
P.viva
x0
0P.
falciparum
0.4%
P.falciparum
India
Rau
rkela
P.vivax
An.
fluviatilis
Peren
nial
7.3–12
71.5%
P.viva
x60
5P.
falciparum
An.
culicifa
cies
5%P.
falciparum
(con
tinued)
10 MOSS AND OTHERS
TABLE3
Con
tinu
edIC
MER
Cou
ntry
Site
Predo
minan
tpa
rasites
Predo
minan
tve
ctors
Season
EIR
Parasiteprev
alen
ceIT
Ncove
rage
(%)
IRScove
rage
(%)
P.malariae
India
Nad
iad
P.vivax
An.
culicifa
cies
Sing
le0.05–0.21
5.7%
P.viva
x1
9P.
falciparum
2.4%
P.falciparum
SouthAsia
India
Goa
P.falciparum
An.
stephensi
Peren
nial
2.5
0.4%
00
P.viva
xIndia
Wardh
aP.
falciparum
An.
culicifa
cies
Peren
nial
NA
0.2%
00
P.viva
xIndia
Ran
chi
P.falciparum
An.
culicifa
cies
Peren
nial
NA
1.4%
NA
NA
P.vivax
An.
fluviatilis
India
Assam
P.falciparum
An.
baim
aii
Peren
nial
0.4
6%(allag
es)
7940
P.vivax
An.
minim
us0.1
Plasm
odium
ovale
Plasm
odium
malariae
Southe
astAsia
China
YingJian
gP.
vivax
An.
minim
usPeren
nial
0.1
NA
8010
0P.
falciparum
An.
maculatus
An.
sinensis
Mya
nmar
Laiza
P.vivax
An.
minim
usPeren
nial
0.4
1%(allag
es)
9610
0P.
falciparum
An.
maculatus
An.
culicifa
cies
Tha
iland
Tha
Song
Yan
gP.
vivax
An.
minim
usPeren
nial
0.3
0.3%
(allag
es)
9072
P.falciparum
An.
maculatus
An.
annu
laris
Southw
estPacific
PNG
EastSe
pik
P.falciparum
An.
punctulatus
Peren
nial
147%
P.falciparum
960
P.viva
xAn.
farauti
4%P.
viva
xP.
ovale
An.
koliensis
1%P.
malariae
P.malariae
1%P.
ovale
(allag
es)
PNG
Mad
ang
P.falciparum
An.
punctulatus
Peren
nial
4019
%P.
falciparum
960
P.viva
xAn.
farauti
13%
P.viva
xP.
ovale
An.
koliensis
–P.
malariae
–So
lomon
Island
sCen
tral
Province
P.viva
xAn.
farauti
Peren
nial
4014
%P.
viva
x(1–80ye
ars)
9081
P.falciparum
Solomon
Island
sWestern
Province
P.viva
xAn.
farauti
Peren
nial
NA
NA
95NA
EIR
=en
tomolog
ical
inoculationrate
(num
berof
infectious
bitespe
rye
ar);IC
EMR
=Internationa
lCen
ters
ofExcellenceforMalaria
Research;
IRS=indo
orresidu
alspraying
;ITN
=insecticide-trea
tedbe
dne
t;IT
Ncove
rage
=prop
ortion
ofho
useh
olds
withat
leasttw
oIT
Ns;IR
Scove
rage
=prop
ortion
ofho
useh
olds
spraye
dwithininsecticidewithinthepa
stye
ar;NA
=no
tav
ailable;
Parasiteprev
alen
ce=prop
ortion
ofindividu
alsin
specifiedag
egrou
pspo
sitive
formalaria
byRDTor
microscop
y;PNG
=Pap
uaNew
Guine
a;PPY
=pe
rson
perye
ar.
11ICEMR MALARIA EPIDEMIOLOGYAND CONTROL
KEY MALARIA METRICS AT ICEMRRESEARCH SITES
All four major parasite species infecting humans are repre-sented in the ICEMR research sites (Plasmodium knowlesiiis not a predominant parasite species at any ICEMR researchsite) (Table 3, Figure 1). As expected, Plasmodium falciparumis the predominant parasite species at the 13 ICEMR researchsites in Africa, with P. vivax and P. falciparum found through-out ICEMR research sites in South America and Asia. Allfour major parasite species are transmitted within ICEMRresearch sites in Papua New Guinea and southeast Asia.Malaria transmission intensity as measured by the annual
EIR varies widely across ICEMR research sites, rangingfrom below one infectious bite per year at sites in southeastAsia, Nadiad in India, Buenaventura in Colombia, Sullana inPeru, and Choma District in Zambia to 310 infectious bitesper year in Tororo, Uganda (Table 3, Figure 2). These differ-ences reflect variation in major vector species, abundance,breeding habitats, and feeding behaviors as well as differ-ences in the methods used to estimate EIR. Seasonal differ-ences also determine malaria transmission intensity and varyacross ICEMR sites (Table 3, Figure 3). Both transmissionintensity and seasonal patterns determine the interventionsneeded to achieve control or elimination. The parasite preva-lence varies widely across ICEMR sites, from less than 1%in regions moving toward elimination to as high as 60% inTororo, Uganda (Table 3, Figure 4).The ICEMR field sites reflect the range of commonly
used malaria control interventions. Although the ICEMRinvestigators are not engaged in implementing malaria con-trol interventions, the ICEMR field sites provide a platformto evaluate the effectiveness of current and future inter-ventions implemented by national control programs. RDTsand artemisinin combination therapies are used for casemanagement at many ICEMR sites. Malaria is confirmed
by microscopy at ICEMR sites in Latin America and India.Intermittent presumptive treatment of malaria in pregnancyis used at ICEMR sites in sub-Saharan Africa and thesouthwest Pacific but not at sites in Latin America or India,where the combination of chloroquine and primaquine isused to treat disease due to P. vivax (with the exception ofpregnant women). Reactive case detection, in which indi-viduals residing within a define radius of a symptomaticindex case are tested and treated for malaria, is conductedby the national malaria control programs in low transmis-sion settings at ICEMR sites in Mali, Zambia, and south-east Asia that are moving toward elimination, as well as inColombia for urban malaria elimination. For vector control,ITNs are distributed at almost all ICEMR sites but withvarying levels of coverage (Table 3), and IRS is used atICEMR sites in east and southern Africa and at some sitesin India, southeast Asia, and southwest Pacific (Table 3).
DISCUSSION
The epidemiology of malaria is heterogeneous and highlyfocal, representing a diversity of parasites, vectors, seasonalpatterns, and transmission intensities.15 Strategies for controland elimination must be adapted to the local epidemiologicaland entomological conditions. The ICEMR research sitesrepresent this range of epidemiological diversity across trop-ical and subtropical regions in four continents. Even atsmaller spatial scales, within countries, provinces and dis-tricts, the epidemiology of malaria can be widely diverse, asexemplified by ICEMR research sites in Uganda, Malawi,and Zambia. Comparisons of the impact of malaria controlinterventions across a range of epidemiological settings arepossible using standardized metrics for a given intervention(such as coverage with insecticidal net distribution) andsimple or sophisticated measures of transmission intensity
FIGURE 1. Predominant parasite species at the International Centers of Excellence for Malaria Research (ICEMR) research sites.
12 MOSS AND OTHERS
(such as force of infection). The range of epidemiologicalsettings encompass areas where P. vivax or P. falciparumpredominate or where mosquito vectors seek blood mealsindoors at night or outdoors during early evening. Impor-tantly, epidemiological studies at the ICEMR field sites areintegrated with entomological studies, including measure-ment of the EIR, human biting index, and insecticide resis-tance, as well as studies of parasite genetic diversity andantimalarial drug resistance. These integrated studies willlead to more detailed and richer understandings of malariatransmission dynamics across the range of epidemiologicalsettings than can be accomplished through studies of only
one of these domains. Furthermore, this platform providesthe framework for novel studies of malaria epidemiology,including cross-ICEMR investigations of serological responsesto an array of parasite antigens and detailed studies of popula-tion movement. Epidemiological studies at ICEMR sites willprovide a deeper understanding of why specific interventionssucceed or fail and will identify surveillance strategies that canbe incorporated into standard practice and are sensitive tochanges in key malaria indicators.
Received January 2, 2015. Accepted for publication May 29, 2015.
Published online August 10, 2015.
FIGURE 2. Approximate annual entomological inoculation rates at International Centers of Excellence for Malaria Research (ICEMR)research sites.
FIGURE 3. Seasonality of malaria transmission at the International Centers of Excellence for Malaria Research (ICEMR) research sites.
13ICEMR MALARIA EPIDEMIOLOGYAND CONTROL
Acknowledgments: We thank Tim Shields of the Department of Epi-demiology, Johns Hopkins Bloomberg School of Public Health forcreating the maps. This paper bears the NIMR Publication ScreeningCommittee approval number 015/2015.
Financial support: The ICEMR programs (U19AI089672, U19AI089674,5U19AI089676, U19AI089680, U19AI089681, U19AI089683,U19AI089686, U19AI089688, U19AI089696, and U19AI089702) werefunded by the National Institute of Allergy and Infectious Diseases,National Institutes ofHealth.
Authors’ addresses: William J. Moss, Department of Epidemiology,Johns Hopkins Bloomberg School of Public Health, Baltimore, MD,E-mail: [email protected]. Grant Dorsey, Department of Medicine,San Francisco General Hospital, University of California, SanFrancisco, CA, E-mail: [email protected]. Joseph M. Vinetz,Department of Medicine, University of California, San Diego School ofMedicine, La Jolla, CA, E-mail: [email protected]. Ivo Mueller, Infec-tion and Immunity Division, Walter and Eliza Hall Institute, Parkville,Australia, E-mail: [email protected]. Miriam K. Laufer, Divisionof Infectious Diseases and Tropical Pediatrics, Center for VaccineDevelopment, University of Maryland School of Medicine, Baltimore,MD, E-mail: [email protected]. Donald J. Krogstad,Department of Tropical Medicine, Tulane University School of PublicHealth and Tropical Medicine, New Orleans, LA, E-mail: [email protected]. Angel M. Rosas-Aguirre, Alexander von Humboldt Insti-tute of Tropical Medicine, Universidad Peruana Cayetano Heredia,Lima, Peru, E-mail: [email protected]. Socrates Herrera,Caucaseco Scientific Research Center, Cali, Colombia, E-mail: [email protected], Myriam Arevalo-Herrera, Malaria Vaccine and DrugDevelopment Center; School of Health, Universidad del Valle, Cali,Colombia, E-mail: [email protected]. Laura Chery, Departmentof Chemistry, South Asia International Center of Excellence forMalaria Research, University of Washington, Seattle, WA, E-mail:[email protected]. Ashwani Kumar, Department of HealthResearch, National Institute of Malaria Research, Indian Council ofMedical Research, Government of India, Field Station, DHS Build-ing, Campal, Panaji, Goa, India, E-mail: [email protected] K. Mohapatra, Department of Health Research, RegionalMedical Research Centre, Northwest, Indian Council of MedicalResearch, Government of India, Dibrugarh, Assam, India, E-mail:[email protected]. Lalitha Ramanathapuram, Department of Biol-ogy, New York University, New York, NY, E-mail: [email protected]. C. Srivastava, National Institute of Malaria Research, Civil Hospi-tal, Nadiad, Gujarat, India. Liwang Cui, Department of Entomology,Penn State University, University Park, PA, E-mail: [email protected] Zhou, The University of California, Irvine, CA, E-mail: zhoug@
uci.edu. Daniel M. Parker, Shoklo Malaria Research Unit, MahidolOxford Tropical Medicine Research Unit, Tak Province, Thailand,E-mail: [email protected]. Joaniter Nankabirwa, Departmentof Internal Medicine, Clinical Epidemiology Unit, Makerere Uni-versity College of Medicine, Kampala, Uganda, E-mail: [email protected]. James W. Kazura, International Health and Medicine,Center for Global Health and Diseases, School of Medicine, CaseWestern Reserve University, Cleveland, OH, E-mail: [email protected].
This is an open-access article distributed under the terms of theCreative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided theoriginal author and source are credited.
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15ICEMR MALARIA EPIDEMIOLOGYAND CONTROL
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