M E T H O D S I N M O L E C U L A R M E D I C I N E
TM
Edited by
Denise L. Doolan
Malaria
Methods
and Protocols
Humana Press
Humana Press
Edited by
Denise L. Doolan
Malaria
Methods
and Protocols
Vector Incrimination and EIR 3
3
From: Methods in Molecular Medicine, Vol. 72: Malaria Methods and Protocols
Edited by: Denise L. Doolan © Humana Press, Inc., Totowa, NJ
1
Vector Incrimination and Entomological
Inoculation Rates
John C. Beier
1. Introduction
This chapter provides standard methods for the incrimination of Anopheles mos-
quito species serving as malaria vectors and associated methods for measuring the
intensity of transmission. In any malaria-endemic area, one or more species of Anoph-
eles mosquitoes serve as malaria vectors. To show that an Anopheles mosquito species
serves as a malaria vector in nature, it is necessary to demonstrate:
1. An association in time and space between the Anopheles species of mosquito and cases of
malaria in humans. After study sites are selected, longitudinal field studies are established
to sample mosquito populations. Adult mosquitoes are sampled by using trapping tech-

niques such as landing/biting collections, light traps, pyrethrum spray catches inside
houses, and outdoor aspiration collections. Larval mosquitoes developing in aquatic habi-
tats normally are sampled by dipping methods. Mosquitoes are identified by standard taxo-
nomic methods and also by molecular methods if mosquitoes belong to a species complex.
The standard methods for performing landing/biting collections are described in this chap-
ter; other types of mosquito trapping methods are described in refs. 1 and 2.
2. Evidence of direct contact between the Anopheles species and humans. Catching a mos-
quito biting humans through landing/biting catches conclusively establishes contact
between that mosquito species and humans. A second method involves immunologically
identifying human blood in the abdomen of field-captured Anopheles mosquitoes. A direct
enzyme-linked immunosorbent assay (ELISA) suitable for bloodmeal identification of
African malaria vectors is described in this chapter (3).
3. Evidence that the Anopheles species harbors malaria sporozoites in the salivary glands. Sporozoites
may be detected in mosquitoes through the dissection and microscopic examination of mosquito
salivary glands (4) or through ELISA methods (5). Both methods are described in this chapter.
The process of vector incrimination is often done in conjunction with longitudinal
field studies to measure the intensity of transmission. In an endemic area, the intensity
of transmission is determined by calculating the entomological inoculation rate (EIR),
which is the product of the mosquito biting rate times the proportion of mosquitoes
with sporozoites. EIRs, calculated as the sum total for each individual vector species of
mosquito, are expressed in terms of average numbers of infective bites per person per
unit time. For example, EIRs in endemic areas of Africa generally range from 1 to
>1000 infective bites per year (6). In this chapter, methods are described for calculat-
4 Beier
ing EIRs from landing/biting catches and determinations of sporozoite rates. Further
details and references are provided on the use of EIRs for epidemiological studies and
for determining levels of control necessary for achieving reductions in malaria preva-
lence and the incidence of severe disease.
2. Materials
2.1. Equipment

1. Mouth aspirators for collecting mosquitoes.
2. Flashlights.
3. Hand-held global position satellite (GPS) system receiver.
4. Low-intensity kerosene lantern.
5. Screened paper pint cups for holding live mosquitoes.
6. Labels and/or permanent marker pens.
7. Glass microscope slides.
8. Phase-contrast compound microscope and dissecting microscope with light source.
9. Surgical scalpel blades.
10. Glass rods or plastic pestles for grinding mosquitoes.
11. 1.8-mL plastic tubes with snap-on caps for holding mosquito samples.
12. 15- and 50-mL tubes for mixing ELISA reagents.
13. Freezer for storing mosquito samples at –20 or –70°C.
14. Refrigerator.
15. 8-Channel manifold attached to 60-mL plastic syringe.
16. Polyvinyl chloride (PVC) microtiter plates.
17. Absorbent tissue paper.
18. ELISA plate reader.
2.2. Reagents
1. Chloroform, ether, and/or 70% ethanol for killing mosquitoes.
2. Physiological saline or medium-199 (M-199) for dissecting mosquitoes.
3. Phosphate-buffered saline (PBS).
4. PBS–Tween-20 (PBS–Tw20) wash solution for ELISA: Add 500 µL of Tween-20 to 1 L
of PBS, mix, and store in a refrigerator.
5. Boiled casein blocking buffer (BB) for ELISA: Suspend 5.0 g casein in 100 mL of 0.1 N
sodium hydroxide and bring to a boil while stirring on a hot plate. After casein has dis-
solved, slowly add 900 mL of PBS, allow to cool, and adjust the pH to 7.4 with hydrochlo-
ric acid (HCl). Add 0.1 g thimerosal and 0.02 g phenol red. Mix well using a magnetic
stirrer and store in a refrigerator; shelf life is 7 to 10 d.
6. Blocking buffer Nonidet P-40 (BB–NP-40) for grinding mosquitoes: prepare by adding 5 µL

of NP-40 to each 100 µL BB and mixing. Make fresh daily.
7. Capture and conjugated monoclonal antibodies for sporozoite ELISA tests.
8. Peroxidase substrate (ABTS) and phosphatase substrate.
9. Recombinant proteins as positive controls for sporozoite ELISA tests.
10. Host-specific peroxidase conjugates (anti-host IgG, H&L) and phosphatase-labeled anti-
bovine IgG (H&L) for bloodmeal ELISA.
11. Host sera as controls for the bloodmeal ELISA.
3. Methods
3.1. Site Selection and Mosquito Sampling Stations
1. Study sites are selected based on study objectives that may be related to epidemiological
studies, malaria control operations, vaccine or drug testing under natural conditions, or an
Vector Incrimination and EIR 5
abundance of vector species of mosquitoes. Study sites may range in size from a cluster of
a few houses to whole communities. Prior to selecting and working in sites, it is advisable
to discuss study objectives and operations with community leaders and residents and to
obtain their consent for the field studies (see Note 1).
2. Normally, it is necessary to develop study site maps based on either traditional mapping
methods or through geographic information systems (GIS) using GPS receivers for deter-
mining latitudes and longitudes of houses and other landmark features within sites. The
maps are used to facilitate field studies logistically and serve as a foundation for the analy-
sis of spatial data on mosquito populations and transmission.
3. Sampling stations for mosquito trapping are selected within sites. For highly endophilic
and anthropophilic mosquitoes like the African malaria vectors, sampling stations are nor-
mally houses or homesteads comprising family units of houses. For exophilic or zoophilic
Anopheles species, sampling stations can be either outdoor areas or animal sheds. The
number of sampling stations depends upon logistical capabilities such as the number of
mosquito collectors available and the expected frequency of sampling within the study
sites. Sampling stations are normally fixed and used repeatedly throughout the duration of
field studies. Alternatively, sampling stations can be selected randomly during each sam-
pling period. While this is sometimes useful from a statistical perspective, we have found

that this approach makes it more difficult to obtain good cooperation from communities.
3.2. Landing/Biting Catches of
Anopheles
Mosquitoes
Landing/biting catches of Anopheles mosquitoes on human volunteers (see Note 2)
are performed either by individual human collectors, by pairs of collectors, or by up to
four collectors working simultaneously. Collections are normally performed at night,
during the biting cycles of the Anopheles mosquitoes. Each collector is responsible for
catching, by mouth aspirator with the aid of a flashlight, mosquitoes that are attracted
to and in the process of biting humans (i.e., host-seeking mosquitoes). The trapping
technique simulates the natural situation whereby mosquitoes contact and bite humans,
and so it is regarded as the gold standard. For each malaria vector field study, it is
necessary to evaluate all other trapping methods for evaluating host contact against the
gold standard. Procedurally, landing/biting catches are performed as follows:
1. Collectors with their arms and legs exposed are seated in chairs or on mats on the ground
at sampling stations. It is common to perform indoor and outdoor biting catches simulta-
neously at the same sampling stations, with the outdoor collectors positioned at least 5 m
from surrounding houses. Trapping inside houses provides information on the numbers of
mosquitoes biting inside, while performing the sampling outdoors provides comparable
information on outdoor biting rates.
2. Collectors catch landing/biting mosquitoes from themselves and from their partners with
a hand-held mouth aspirator (or mechanical aspirator). Each collector uses a flashlight to
locate landing/biting mosquitoes. Additional background light from a low-intensity lan-
tern is advisable.
3. Each aspirated mosquito is placed in screened pint cups, labeled according to sampling
station. Some studies also segregate mosquito collections by hour of capture, and this
requires additional cups labeled by hour.
4. Landing/biting collections are normally performed throughout the night as dictated by the
natural biting habits of the target mosquitoes. Logistically, it is feasible for individuals or
teams of collectors to work one-half hour every hour throughout the night. Alternatively,

it is feasible for half the team to work continuously during the first half of the night and
the rest of the team to work the second half of the night.
6 Beier
5. After collections, mosquitoes in cups are normally killed either by freezing or by exposure
to chloroform or ether. For immediate processing, mosquitoes may be aspirated out of
cups and blown into 70% ethanol followed by transfer to PBS or M-199. Mosquitoes may
also be stored in Carnoy’s solution for cytogenetic studies or for longer-term storage before
processing (see Chapter 8).
6. Mosquitoes are identified according to taxonomic methods or by molecular techniques
(see Chapter 8).
7. The biting rate for each mosquito species is calculated as the number of mosquitoes per
person per unit of sampling effort. For example, a biting rate of 2 per day is derived from
one collector who catches one mosquito while working throughout the night in half-hour
shifts. A biting rate of 40 per day is derived from a team of two collectors working in half-
hour shifts during the whole night and catching 40 mosquitoes.
3.3. Determination of Sporozoite Rates in Anopheles Mosquitoes
3.3.1. Dissection and Microscopic Examination of Mosquito Salivary Glands
1. Salivary gland dissections are performed on mosquitoes freshly killed by freezing, expo-
sure to ether, or by blowing into 70% ethanol.
2. Place an individual mosquito on a glass slide, with head in contact with a small drop of
physiological saline or PBS or M-199.
3. View slide containing mosquito on a dissecting microscope at ×10 to ×30.
4. Hold two dissecting needles, which can be made conveniently by placing the 27-gage
needle from a 1-mL tuberculin syringe on the end of the movable shaft (rubber stopper
removed), between your thumb and forefinger. Place one needle (bevel down) on the tho-
rax of the mosquito while placing the other needle against the mosquito head (bevel facing
toward the head). Simultaneously place pressure on the thorax while pulling the head away
from the thorax. As the head moves away from the thorax, observe the salivary glands and
cut them with the needle controlling the head. The cut should be made in one continuous
motion as soon as the glands are seen; otherwise, it is necessary to reposition the head and

try again. Sometimes the glands become stuck in the mosquito thorax, and it is necessary
to tease apart the tissue to locate and cut the glands.
5. After severing the salivary glands, remove the head and thorax and any other extraneous tissue.
6. Place a glass cover slip over the salivary glands, now lying in the dissection media.
7. Transfer the slide to a compound microscope and observe the preparation at ×100 to locate
the salivary glands.
8. Apply gentle pressure to the cover slip to disrupt the glands and then search at ×400 the
entire area of the salivary glands for sporozoites (which normally measure about 1 × 10 µm).
Experienced dissectors can typically dissect a mosquito within 1 min and reliably exam-
ine the preparation within 2 min.
9. Sporozoite infections are normally scored according to the number of sporozoites observed:
1+ (1–10 sporozoites), 2+ (11–100 sporozoites), 3+ (101–1000), and 4+ (>1000 sporozoites).
10. Record results. Normally, each field-collected mosquito is given a unique identifier (see
Note 3).
11. Standard procedures are also available for removing sporozoite material from slides and
testing the sporozoites by ELISA to determine Plasmodium species (7). Various addi-
tional procedures are available for determining sporozoite loads, the number of sporozoi-
tes found in the salivary glands of individual mosquitoes (8,9).
3.3.2. Sporozoite ELISA Methods
ELISA methods exist for testing field-collected mosquitoes for sporozoites repre-
senting each of the four species of Plasmodium affecting humans (5,10,11). The sporo-
Vector Incrimination and EIR 7
zoite ELISA detects circumsporozoite protein that is either from intact sporozoites or
in soluble form within the mosquito. Based on comparisons with the gold standard
dissection method, the sporozoite ELISA provides a reasonable estimate of the true
sporozoite rate in wild-caught mosquitoes (12).
1. Prepare the mosquito sample for ELISA testing. Label sets of 1.8-mL tubes with the cor-
responding mosquito sample numbers. Add 50 µL of BB–NP-40 to each vial. Using a
sharp clean surgical blade, cut the mosquito between the thorax and the abdomen (nor-
mally done on a filter paper). Transfer the head–thorax with forceps to the labeled tube,

and transfer the abdomen to the corresponding tube for bloodmeal identification if the
mosquito is blood-fed. If the mosquito is not blood-fed or no bloodmeal analysis is
required, discard abdomen. Grind the mosquito in the tube using a nonabsorbent glass rod
or plastic pestle. Add 200 µL of the BB to bring the total sample volume to 250 µL. To
avoid contamination, clean the pestle and wipe it dry before grinding the next sample.
Repeat the procedure until all samples are prepared. Arrange samples in numbered order
within storage boxes and keep samples in a freezer at –20 or –70°C until testing.
2. Coat number-coded ELISA plates with monoclonal antibody (MAb). In each well, add 50 µL
of the diluted capture MAb. Cover the plates with another clean ELISA plate and incubate
for 30 min at room temperature in subdued light.
3. Block the plates. Using an 8-channel manifold attached to a vacuum pump, aspirate the
capture MAb from the microtiter plate. Bang the plate hard on an absorbent tissue paper or
gauze to ensure complete dryness. Fill each well with BB using a manifold attached to a
60-mL syringe. Incubate for 1 h at room temperature in subdued light.
4. Load the plates with mosquito samples. Aspirate the blocking buffer from the wells using
the manifold attached to a vacuum pump and bang plate to complete dryness. Place 50 µL
of 100, 50, 25, 12, 6, 3, 1.5, 0 pg of positive control recombinant protein in the first
column wells. Into the second column, add 50 µL per well of the negative controls; nor-
mally, field-collected male Anopheles mosquitoes or culicine mosquitoes are used as nega-
tive controls. Load 50 µL of each mosquito sample to the remaining wells of the plate,
checking carefully that numbered mosquito samples are placed in the wells according to
the completed ELISA data form. Cover the plate and incubate for 2 h at room temperature
in subdued light.
5. Add peroxidase-conjugated monoclonal antibody. After 2 h, aspirate the triturate from the
wells and wash the plate two times with PBS-Tw20. Add 50 µL of the peroxidase-labeled
enzyme and incubate for 1 h at room temperature.
6. Add the substrate. Aspirate the enzyme conjugate from the wells and wash three times
with PBS-Twn 20. Using a multichannel pipet, add 100 µL of ABTS substrate and incu-
bate for 30 min. Positive reactions, which appear green, can be determined by reading
plates at 414 nm using an ELISA plate reader; absorbance values two times the mean of

negative controls provides a valid cutoff for sample positivity (13). Alternatively, results
can be read visually with a high degree of accuracy (14). Record results for each tested
mosquito.
3.4. Bloodmeal ELISA Methods
Both direct and indirect ELISA procedures are routinely used to identify bloodmeals
of wild-caught mosquitoes. Strategies for using ELISAs for bloodmeals depend upon
study objectives. For example, Edrissian et al. (15) used a direct ELISA to screen over
5000 Anopheles for human blood; they reported that an experienced technician could
easily screen over 1000 samples per week. Burkot and DeFoliart (16) used an indirect
ELISA to identify 16 host sources, including wild animals. Their studies involved pro-
8 Beier
ducing antisera for each host tested. To bypass extensive production of antisera and to
shorten the overall testing time, we developed a simple direct ELISA that uses only
commercially available reagents (3). The test reliably detects bloodmeals from humans
and from a spectrum of domestic animals for which conjugated antisera are commer-
cially available. The test employs a two-step screening for human and cow bloodmeals,
making it particularly useful in Africa where major malaria vectors feed primarily on
humans and cows. The assay is performed as follows:
1. Prepare wild-caught half-gravid to freshly fed mosquitoes by cutting them transversely at
the thorax between the first and third pairs of legs (under a dissecting microscope, ×10–
20). In a labeled tube, place the posterior part of the mosquito containing the bloodmeal in
50 µL PBS and grind with a pestle or pipet repeatedly. Dilute sample 1:50 with PBS and
freeze samples at –20°C until testing.
2. Load 96-well polyvinyl microtiter plates with mosquito bloodmeal samples by adding 50 µL
of each sample per well. On the same plate, add 50-µL samples of positive control antis-
era for human and cow (diluted 1:500 in PBS), and four or more negative control unfed
female mosquitoes or male mosquitoes obtained from the same field collections and
handled as above. Cover and incubate at room temperature for 3 h (or overnight).
3. Wash each well twice with PBS-Tw20.
4. Add 50 µL of host-specific conjugate (anti-host IgG, H&L) diluted 1:2,000 (or as deter-

mined in control tests) in 0.5% BB containing 0.025% Tween-20, and incubate 1 h at
room temperature.
5. Wash wells three times with PBS–Tw-20.
6. Add 100 µL of ABTS peroxidase substrate to each well.
7. After 30 min, read each well with an ELISA reader. Samples are considered positive if
absorbance values exceed the mean plus three standard deviations of four negative con-
trol, unfed female, or male mosquitoes. The dark green positive reactions for peroxidase
(or the dark yellow reactions for phosphatase) may also be determined visually (14).
8. The following modification is used in the two-step procedure for determining a second
host source in the same microtiter plate well where mosquito samples were screened for
human blood (3). A second conjugate, phosphatase-labeled anti-bovine IgG (1:250 dilu-
tion of a 0.5 mg/mL stock solution) is added to the peroxidase-labeled anti-human IgG solu-
tion (step 4). Screen bloodmeals first for human IgG by adding peroxidase substrate, and after
reading absorbance at 30 min, wash the wells three times with PBS–Tw20. Add 100 µL of
phosphatase substrate and read plates after 1 h to determine positive cow reactions.
9. Each laboratory should initially establish the sensitivity and specificity of the assay for
each conjugated antisera and different lots of reagents. The assay can detect sera diluted to
around 1:10,000,000. The degree to which commercially available antisera crossreact with
sera from different hosts varies according to manufacturers. For standardization and to
reduce levels of nonspecific reactivity, it is sometimes necessary to add 1:500 dilutions of
heterologous sera to the conjugate solutions (see step 4 ). It is important to note that the
assay works equally well with frozen, dried, or Carnoy’s fixed mosquito samples, and that
each 1-mg vial of conjugated antisera can be aliquoted, frozen, and used to test up to
20,000 mosquito samples.
3.5. Entomological Inoculation Rates (
see
Note 4)
3.5.1. Calculation of EIRs
The EIR is calculated as the product of the mosquito biting rate and the sporozoite
rate. Table 1 provides an example for the calculation of the EIR from site-specific data

on mosquito biting rates and sporozoite rates. Beyond calculating daily EIRs, it is also
Vector Incrimination and EIR 9
useful to calculate monthly or annual EIRs based on averaged values of biting rates and
sporozoite rates. For the example given in Table 1, if these were the only sample data
available, then an estimate of the monthly EIR could be obtained by multiplying the
daily EIR of 0.60 by 30 d to yield an estimated monthly EIR of 18. For field studies, it
is advisable to have two or more point determinations of biting rates per month and
statistically reliable estimates of sporozoite rates.
3.5.2. Relationships Between EIRs and Measures of Human Malaria
Time series data on EIRs for given sites can be related directly to measures of human
malaria in several simple ways. Graphically, measures of the EIR and human malaria
such as prevalence or incidence can be graphed along the y-axis and related to sam-
pling time points on the x-axis. In addition, such temporal changes in EIR and infection
or disease can be related to environmental parameters such as temperature and rainfall.
The same data can be graphed with EIRs on the x-axis and human malaria data on the y-
axis. This approach, when combined with regression analysis, provides both a graphical
and a statistical account of the variation in human infection or disease explained by EIRs.
Several studies in Africa provide good examples of how EIRs can be related to the
following:
1. Incidence of P. falciparum infection in children (17).
2. Incidence of severe life-threatening cases of P. falciparum in children (18,19).
3. Prevalence of P. falciparum (6).
It is important to note that malaria prevalence data, which is often used as the basis
for guiding control operations, is not a sensitive indicator of the intensity of malaria
transmission by vector populations. Malaria prevalence rates from 40 to >90% can
occur at any EIR exceeding one infective bite per person per year. Control operations
therefore need to be guided by both entomological data on EIRs and traditional mea-
sures of human malaria infection and disease.
4. Notes
1. Ethical concerns must be addressed for each malaria vector field study. Mosquito trapping

in malaria endemic areas normally involves local mosquito collectors who are recruited
from study communities. For landing/biting mosquito sampling methods, local mosquito
Table 1
Entomological Inoculation Rate
Species Biting rate
a
Sporozoite rate (%)
b
Daily EIR
A10 5.00 0.50
B4 2.00 0.08
C2 1.00 0.02
Total 16 3.75 0.60
The EIR is calculated as the product of the biting rate times the sporozo-
ite rate. In this hypothetical example, there are three vector species of
Anopheles mosquitoes. The daily EIR of 0.60 infective bites per person per
night is calculated as the sum total of EIRs for each of the three species.
a
Number of mosquitoes per person per night.
b
Percentage of mosquitoes with salivary gland sporozoites by dissection
or ELISA.
10 Beier
collectors normally do not face any excess risks for malaria infection beyond what they
would normally experience sleeping in their own homes. Some studies have traditionally
offered malaria prophylactic drugs to collectors. However, in highly endemic areas, this
practice goes beyond normal protective measures of the community and may even be
detrimental to the long-term health of the collectors. It is advisable that malaria field stud-
ies make sure that mosquito collectors have proper access to curative antimalarial drugs
and health facilities whenever they develop symptomatic malaria infections.

2. The landing/biting catch method is the gold standard for determining human contact with
mosquitoes. Other methods such as pyrethrum spray catches or CDC light traps may be
used to estimate rates of human biting for each Anopheles species. However, for each
study area, it is necessary to establish quantitative relations between the sampling method
proposed and the gold standard method. Estimates of correction factors from regression
analysis based on data from comparative sampling for one site do not generally hold uni-
versally throughout the ranges of mosquitoes (20).
3. Care must be taken with data management. Malaria vector studies normally yield large
numbers of mosquitoes from different trapping methods that are processed by a variety of
different methods ranging from taxonomic identifications to sporozoite ELISA testing.
Primary data sets can be established in matrix format with each mosquito represented by
rows and columns represented by collection and processing data. Prospects of having >15
variables of data for each individual mosquito and over 50,000 mosquitoes in a single
dataset demand careful attention in terms of data entry, data management, and analysis.
4. The EIR is a direct measure of the intensity of malaria transmission by vector populations.
In malaria endemic areas outside Africa and Papua New Guinea, annual EIRs may be
lower than one infective bite per person per year (21). The low EIRs are often due to
sporozoite rates substantially less than 1%. In some areas of Central and South America,
for example, it is not uncommon to find fewer than 1 in 1000 mosquitoes infected with
malaria parasites. Under such conditions, investigators may alternatively calculate the vec-
torial capacity (VC), an indirect measure of the potential for transmission that considers the
biting rate of the vector population, the human blood-feeding rate, the vector survival rate,
and the extrinsic incubation period of the malaria parasite (22). Some of the practical limita-
tions and errors associated with the use of the VC are discussed by Dye (23).
Acknowledgments
This work was supported by the National Institutes of Health grants AI29000,
AI45511, and TW01142.
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Control Assoc. 9, 260–263.
21. Alles, H. K., Mendis, K. N., and Carter, R. (1998) Malaria mortality rates in South Asia and in
Africa: implications for malaria control. Parasitol. Today 14, 369-375.
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Measures of Risk of Malaria 13
13
From: Methods in Molecular Medicine, Vol. 72: Malaria Methods and Protocols

Edited by: Denise L. Doolan © Humana Press, Inc., Totowa, NJ
2
Epidemiological Measures of Risk of Malaria
J. Kevin Baird, Michael J. Bangs, Jason D. Maguire, and Mazie J. Barcus
1. Introduction
Estimates of the risk of infection by the parasites that cause malaria govern deci-
sions regarding vector control, chemoprophylaxis, therapeutic management, and clini-
cal classifications of immunological susceptibility to infection. Gauging the risk of
malaria represents a critical step in its management and the investigation of its conse-
quences. The term malariometry is applied to the numerical measure of risk of malaria
in communities (9). Many approaches have been developed and applied to
malariometry, but no single method stands out as universally applicable. Instead, indi-
vidual measures of risk must be suitable for specific questions posed in the context of
what may be practically measured. For example, passive surveillance provides a supe-
rior measure of risk where the infrastructure of diagnosis and reporting is well devel-
oped and the risk of infection relatively low, e.g., in the United States, where conducting
active cross-sectional surveys would yield little useful information at great cost. Active
surveillance for cases is suited to areas with relatively high risk, unreliable diagnostic
capabilities and inadequate reporting infrastructure. This chapter strives to catalog
measures of risk of malaria and define their utility in the context of local parameters of
endemicity, infrastructure, and intent of inquiry.
The risk of malaria is highly dependent on interactions between the host, parasite,
mosquito vector, and environment, a relationship known as the epidemiologic triad of
disease. Changes in any one of these elements may profoundly impact risk of infection.
Measures of risk of malaria may be broadly classified as either indirect or direct. Indi-
rect measures gauge risk through surrogate markers of risk of infection such as rainfall,
altitude, temperature, entomological parameters, spleen rates, antibody titers, or pat-
terns of antimalarial drug use in a community. Direct measures of risk depend on diag-
noses of malaria (clinical or microscopic) and their relationship to a variety of
denominators representing classes of persons at risk over some unit of time. In general,

indirect measures apply data conveniently at hand to estimate risk of malaria. By con-
trast, direct estimates of risk often require deliberate effort to collect data for the sole
purpose of gauging risk of malaria.
An area supporting active malaria transmission is termed endemic. Transmission of
infection may be unstable or stable, the primary difference being a fluctuating low to
high incidence versus a consistently high incidence over successive years.
Malariologists have long graded endemic malaria according to risk of infection as reflected
14 Baird et al.
in the proportion of children and adults having enlarged spleens (spleen rate, see below).
However, these terms have evolved into a more general use and are routinely applied in the
absence of supporting spleen rate measures. The following terms have been used to empiri-
cally gauge regional risk according to criteria described by Bruce-Chwatt (9):
1. Hypoendemic: Little transmission, and the effects of malaria on the community are unimportant.
2. Mesoendemic: Variable transmission that fluctuates with changes in one or many local
conditions, e.g., weather or disturbance to the environment.
3. Hyperendemic: Seasonally intense malaria transmission with disease in all age groups.
4. Holoendemic: Perennial intense transmission with protective clinical immunity among adults.
2. Indirect Estimates of Risk of Malaria
2.1. Environmental (Rainfall, Altitude, Temperature)
Transmission of malaria requires mosquito vectors in the genus Anopheles. These
insects exhibit exquisite sensitivity to the environmental parameters of temperature
and humidity. Thus, rainfall, altitude, and temperature govern the activity and abun-
dance of anopheline mosquitoes and the transmission of malaria. Within ranges of tem-
perature (20–30°C) and humidity (>60%) that vary for each vector species, the
mosquito survives and is capable of transmitting malaria. When the limits of tempera-
ture and humidity tolerance are exceeded, the vectors die, and the risk of malaria evapo-
rates. Variations of temperature and humidity within the viable range for mosquitoes
can also affect the duration of sporogony, the time required for development of the
parasite in the mosquito after taking a bloodmeal from an infected human so that a new
host can be infected. Cooler temperatures generally prolong sporogony, decreasing the

period of infectivity. High relative humidity increases mosquito life-span, so that each
infective mosquito can infect more hosts. The risk of transmission by anophelines, how-
ever, depends on an available pool of infectious humans so that even in a favorable envi-
ronment with the appropriate vector, transmission cannot be sustained without adequate
numbers of already infected humans. Conditions perfectly suitable for anopheline sur-
vival allow seasonably abundant mosquito populations in the United States, but infection
is rare because of the lack of infectious humans in the region.
2.2. Entomological
Chapter 1 details the use of the entomological inoculation rate as a measure of risk
of infection. The following terms have been used to describe risk of malaria according
to entomological criteria:
1. Human landing rate = anophelines captured/person-night.
2. Infected mosquito = oocysts in stomach wall by dissection.
3. Infective mosquito = sporozoites in salivary gland by dissection.
4. Sporozoite rate = infective anophelines/anophelines captured.
5. Entomological inoculation rate = human landing rate × sporozoite rate.
= infective mosquito bites/person-night.
2.3. Clinical
2.3.1. Spleen Rate
The spleen rate is the proportion of people in a given population having enlarged
spleens expressed as a percentage. The relationship between malaria and the spleen
Measures of Risk of Malaria 15
rate has served as an indirect marker of risk of malaria long before plasmodia were
known as the cause (Dempster introduced the method in India in 1848). Chronic expo-
sure to malaria causes spleen enlargement. Thus, the percentage of people having
enlarged spleens and the degree of enlargement correlate with risk of infection in a
community. The WHO has classified endemicity as gauged by spleen rate as shown in
Table 1.
Important caveats complicate this convenient estimate of risk. Under conditions of
epidemic malaria, where risk of infection may be very high, spleen rates may be close

to nil because exposure is acute rather than chronic. The spleen rate is useful as a
relative measure of risk only where stable malaria prevails. The distinction between
hyperendemic and holoendemic on the basis of spleen rate in adults, developed on the
basis of observations in sub-Saharan Africa, does not appear to hold true on the island
of New Guinea where adults consistently have enlarged spleens in the face of
holoendemic malaria.
A secondary estimate of risk utilizing spleen measurements is the average enlarged spleen
(AES). The AES represents the mean Hackett score derived from a sample of enlarged
spleens. Table 2 describes grading of spleen enlargement on the basis of palpation.
Spleens with Hackett scores of zero are not included in the calculation of AES. A
higher AES between two sites with comparable spleen rates may be interpreted as con-
sistent with higher risk. A recent malariometric survey in Papua New Guinea found
that, although spleen rates did not vary with altitude for children less than 10 yr of age,
AES decreased with increasing altitude, closely paralleling altitude specific prevalence
of malaria (4).
Table 1
WHO Criteria for Classification of Endemicity by Spleen Rates
Endemicity Children aged 2–9yr (%) Adults (>16 yr)
Hypoendemic 0–10 No measure
Mesoendemic 11–50 No measure
Hyperendemic >50 “High” (>25%)
Holoendemic >75 “Low” (<25%)
Table 2
Criteria for Scoring Spleen Size
a
Score Description of spleen as measured with subject in recumbent position
0 Normal, not palpable
1 Palpable below costal margin on deep inspiration
2 Palpable below costal margin but not beyond midpoint between costal margin and
umbilicus

3 Palpable below limits for score of 2 but not beyond umbilicus
4 Palpable below umbilicus but not beyond midpoint between umbilicus and
symphisis pubis
5 Palpable beyond limits for score of 4
a
AES = Σ(Hackett score
i
× n
i
)/N, where Hackett scores of 1 through 5 are included. n
i
= number of
spleens measured with a given Hackett score. N = n
1
+ n
2
+ n
3
+ n
4
+ n
5
(total number of non-Hackett 0
spleens measured)
16 Baird et al.
2.3.2. Serology
Serological tests have been applied to demonstrate exposure to infection among
individual subjects. Unfortunately, no serological test reliably assesses either degree of
naturally acquired immunity or the extent of exposure in individuals. Risk of exposure
among groups, however, may be assessed by serological analyses. Detection of anti-

bodies to the circumsporozoite protein (CSP) in European travelers returning from
malarious areas suggests that anti-CSP antibodies can serve as an indicator of the rela-
tive risk of infection in travelers to specific regions (5–7). The prevalence of antibodies
to malaria antigens such as CSP, merozoite surface antigen (MSA), and erythrocytic
stage antigens has also served as an indirect indicator of risk of infection (2,8) and in
some studies correlates with spleen rates (8), prevalence of positive smears (1,8), and
parasite density (2). Serological assays may also be useful in assessing risk in regions
with recent increases in transmission during epidemics or with declining transmission
during eradication efforts (9–11). However, no currently available serological assay
system can reliably serve as a quantitative measurement of exposure.
3. Direct Estimates of Risk of Malaria
3.1. Passive Surveillance
3.1.1. Passive Case Detection
Passive case detection (PCD) is the detection and reporting of malaria cases
restricted to people seeking treatment for illness at a health post, clinic, or hospital. The
PCD is reported as simply the number of cases treated. The PCD proportion, or ratio of
malaria cases to some defined total (hospitalizations, febrile illnesses, deaths), is often
used to gauge the burden of illness caused by malaria relative to all other causes defin-
able in the setting from which those data were collected. This is often called the PCD
rate, although it is actually a proportion. The quantitative value of the PCD rate varies
according to the rigor of diagnostic procedures and the likelihood of malaria para-
sitemia masking some other underlying cause of illness (see Subheading 3.2.8.). The
availability of reporting health-care delivery facilities also impacts interpretation of
PCD data. PCD data are used to gauge risk in communities with the assumption that
virtually all infections prompt seeking of treatment at a reporting facility.
In a setting where malaria is reported on the basis of microscopically confirmed
infection, and the proportion of fevers caused by malaria is relatively low, the PCD rate
may serve as a reliable estimate of risk of malaria relative to other febrile illnesses in
the community. In general, this scenario is true where malaria is hypo- to mesoendemic
and health-care providers are more likely to report malaria on the basis of diagnostic

criteria that exclude other more common causes of febrile illness. In this scenario, the
reported PCD proportion may carry good sensitivity and specificity.
The PCD proportion as a measure of risk is less reliable where malaria is hyper- to
holoendemic. This problem stems from three important features specific to heavily
endemic areas. First, because malaria dominates as a cause of febrile illness, health-
care providers tend to make presumptive diagnoses of malaria in patients presenting
with fever. Thus, other causes of febrile illness are often erroneously classified as
malaria so that the specificity of the PCD proportion may be extremely low. Second,
because self-treatment often relieves symptoms, the true burden of malaria in the com-
Measures of Risk of Malaria 17
munity may be underreported. Finally, naturally acquired immunity in hyper- to
holoendemic regions leaves most infections unnoticed at treatment facilities.
The PCD totals may be analytically applied in a variety of ways. If the PCD total is
believed to have captured most infections in the community, then monthly or annual
PCD case totals may be divided by the mid-interval population of the areas served by
the reporting facilities to define incidence of infection.
Incidence of malaria = malaria PCD total/mid-interval population/unit time
More often, a PCD proportion is applied as a direct measure of the contribution of
malaria to febrile disease in communities expressed as a percentage.
PCD proportion = (malaria cases/patients seeking care for febrile illness) × 100
3.1.2. Annual Parasite Incidence
The number of malaria cases per 1000 population per year is called the annual para-
site incidence, or API. The API represents the most broadly applied measure of risk of
infection. Many health authorities rely upon the API as the core measure of risk of
infection. The statistic is often used as the basis for comparing risk between communi-
ties, districts, provinces, and nations. The means of deriving the numerator for the API,
“cases of malaria”, varies a great deal. Comparisons of risk based on the API demand
consideration of the sources and case definitions; for example, clinical diagnosis ver-
sus smear-confirmed diagnosis for reported total cases. The API numerator often rep-
resents a hybrid of PCD and active surveillance methods (see below), and the relative

contributions of each impact interpretation of the API.
Annual parasite incidence = reported infections/1000 person (mid-year)/year
A statistic used to help interpret the API is the annual blood examination rate, or ABER.
This is the number of blood films examined per 1000 population. The ABER reflects the
degree of diagnostic effort made to identify malaria. For example, between two locations
having comparable API estimates, the location having the lower ABER may be consid-
ered higher risk because less effort produced an equal density of infections.
Annual blood examination rate = blood film exams/1000 person (mid-year)/year
3.2. Active Surveillance
3.2.1. Active Case Detection
Systematic screening of communities for people with fever and examination of blood
films collected from them is called active case detection (ACD). The analytical appli-
cation of infections discovered by ACD varies. The data collected by ACD may be
applied as follows:
Fever rate = (people with fever/people examined for fever) × 100
Malaria among fevers rate = (people with malaria/people with fever) × 100
These estimates serve as measures of the prevalence of fever in the community at
sampling and the proportion of fevers likely caused by malaria, respectively. Health
officers often use ACD to monitor the progress of control efforts within specific areas,
18 Baird et al.
but also include these detected cases into the numerator for API. Thus, the vigor of case
detection impacts on the API. In this sense, the importance of interpreting the API in
the context of ABER may be appreciated.
3.2.2. Active Case Survey
The primary distinction between active case survey (ACS) and ACD is sampling that
does not exclude people without fever. Whereas ACD estimates the prevalence of fever
and the proportion of fevers caused by malaria, ACS measures the prevalence of para-
sitemia independently of fever. The ACS may be the best approach to assessing risk of
infection in communities where parasitemia often occurs without fever, that is, where
malaria is hyper- to holoendemic. The survey includes recording both febrile and afebrile

(or apyrexic) malaria cases. The analytical application of ACS may include the following:
Point prevalence of malaria = (people with parasitemia/people examined) × 100
Febrile malaria rate = (people with febrile malaria/people with malaria) × 100
Point prevalence refers to the ratio of parasitemic individuals to the total number of
individuals examined at a single point in time. This provides an estimate of risk by
indicating the number of people infected at any given time with higher prevalence
indicating higher rates of transmission. However, for diseases like malaria that may be
seasonal in some locations, the point prevalence in June might not be a good estimator
of risk for an individual traveling to the area in November.
3.2.3. Gametocyte Rate
Analysis of point prevalence data often includes specific designation of the preva-
lence of gametocytemia in study subjects, the carriage of sexual stage parasites that can
be transferred to feeding mosquitoes to complete the life cycle and allow new infec-
tions of human hosts. In highly endemic areas where immunity to disease often devel-
ops, such individuals are frequently asymptomatic and remain undiagnosed and
untreated, serving as reservoirs for new infection in the community. Because
gametocytemia declines with increasing age in malaria endemic regions (1,12), game-
tocyte rates in young children may serve as an indicator of risk, particularly when
comparing gametocyte rates between two different locations.
3.2.4. Period Prevalence
Compared to point prevalence, period prevalence may better reflect risk for persons
who will be exposed to infection over an extended period. This may be especially true
where risk fluctuates appreciably. Whereas point prevalence addresses the question of
whether a person currently has malaria, period prevalence addresses the question of
whether that subject had malaria at any time during the period under investigation.
This serves as a measure of the probability that an individual in a defined population
will be a case at any given time over a defined period. The numerator of this estimate
includes both newly incident cases (see below) and cases that may have developed
before the survey was initiated. The time of onset of infection may not be known,
especially in endemic regions where some subjects may be asymptomatic and remain

undiagnosed. Thus, incident cases and prevalence may not be distinguishable. Assum-
ing a stable population over time, period prevalence is calculated as follows:
Measures of Risk of Malaria 19
Period prevalence = (people with malaria at start of period + new cases of malaria during
period)/population under study) × 100
Period prevalence requires identifying a sample of individuals from a population,
screening each of them for malaria on enrollment, and systematically repeating malaria
smears during the defined period in order to identify new cases. Multiple infections
among any given individual allows the possibility of a period prevalence of >100%.
The greatest limitation with period prevalence is the fact that many population totals
are dynamic. The migration of people, and other important changes like mass drug
administration, chemoprophylaxis, or any other intervention that alters the number of
people at risk, makes the drawing of meaningful statistical inference from measures of
period prevalence difficult. In many instances, the effort required to define period
prevalence would be better spent measuring incidence, which provides much less
ambiguous measures of risk (see Subheading 3.3.).
3.2.5. Cumulative Incidence
Cumulative incidence (CI) represents the probability or proportion having malaria
or a specific outcome of infection, for example, cerebral malaria, relapse, death, or
chemotherapeutic failure over defined intervals. Cumulative incidence is often referred
to as an “attack rate,” even though the estimate represents a proportion rather than a
true rate. The measurement of CI requires a prospective study of people free of infec-
tion at the outset. These may be uninfected people newly arriving in a malarious area or
people cured of malaria immediately before the observation period. The number of
new infections is divided by the number of people at risk, expressed in the context of
the period of observation. For example, if one follows 100 people for 10 weeks and 25
get malaria, then the 10-week cumulative incidence of malaria is 25%. More often,
larger populations are followed for longer periods, and the estimate may be compli-
cated by losses to follow-up, migration, or death by other causes.
When individual follow-up times vary for study subjects, a convenient means of

calculating cumulative incidence is the actuarial method (also called life table). This
approach takes into account the loss of individuals from the study population in the
denominator by presuming that the mean withdrawal time occurred at the midpoint of
the surveillance interval. For example, in a 1-yr study of malaria with monthly inter-
vals of observation, all subjects lost to follow-up would be assumed to have done so at
the midinterval, that is, 2 wk. This approach conveniently averages person-time losses
across the interval. This is especially useful when such losses are likely, for example,
the occurrence of vivax malaria among subjects recruited to gauge the incidence den-
sity of falciparum malaria. The actuarial method for estimating CI is as follows:
Cumulative incidence = attack rate (%) over a defined period
Cumulative incidence (actuarial) = incident cases/[population at start of study – (number of
withdrawals/2)]
3.2.6. Incidence Density
Incidence density of malaria estimates the risk of infection in a population expressed
as a true rate; that is, the number of new infections per unit person- time. This estimate
requires a cohort of people who are free of infection and prospectively followed over a
20 Baird et al.
defined period. This is most often accomplished by giving radical curative therapy
before the follow-up phase, but newly arrived migrants into malarious areas may also
provide a suitable cohort without radical cure. Incidence density is calculated simply
as the number of new infections divided by the sum of person-time at risk. People lost
to follow-up contribute person-time to the denominator up to the point of loss. Their
contribution should not be counted for the full period of the study. For example, if one
follows 100 subjects for 52 wk and 25 become infected, the incidence density is 25
infections per 100 person-years, or 0.25 infections per person-year, assuming each
individual contributed 52 wk of follow-up time. This overly simplistic example assumes
no losses to follow-up. However, a subject infected at wk 2 contributes only 2 wk of
person-time to the denominator, not 52. Assume that infections occur evenly over the
52 wk and that approximately one infection occurs every 2 wk. In this scenario, losses
in person-time at risk due to infection outcomes amount to 650 person-weeks, or

12.5 yr. Taking these losses into account, the incidence density would be estimated
at 25 infections/87.5 person-years, or 0.29 infections/person-year. Further, assume
that 20 people were lost follow-up at anywhere from wk 1 to wk 51 of the observa-
tion period, yielding a total loss of 12.5 person-years at risk. Thus, the true incidence
density in the hypothetical cohort would be estimated as 25 infections per 75 person-
years, or 0.33 infections/person-year (or everyone experiencing, on average, an in-
fection once every 3 yr).
Incidence density = infections/person-year at risk
3.2.7. Attributable Risk
Attributable risk (or risk difference) represents an estimate of the risk of disease that
may be attributed to a specific exposure. In its simplest form, it is the additional amount
of disease in those exposed over the background amount of disease in the unexposed
population and is given by:
AR = I
e
– I
u
where I
e
is the incidence in the exposed population and I
u
is the incidence in the
unexposed population.
In conducting malaria studies in transmission areas, it is difficult to reliably differ-
entiate between reinfection and recurrent parasitemia following therapy. The attribut-
able risk statistic, calculated by subtracting the coincident incidence rate for a given
population from the rate of recurrent parasitemia, estimates the rate of therapeutic fail-
ure. The efficacy of standard mefloquine therapy against uncomplicated Plasmodium
falciparum infections was evaluated in children aged 6 to 24 mo in the Kassena-
Nankana District of northern Ghana, West Africa. The incidence of late recrudescence,

or therapeutic failure, was calculated as the difference between the incidence of recur-
rent parasitemia during wk 3 and 4 after mefloquine therapy and the known attack rate
of malaria in the region for the cohort. The incidence of recurrent parasitemia at d 28
was 6.3 infections/person-year at risk. However, this incidence rate approximated the
known reinfection rate in this cohort (5.7 infections/person-year). Thus, the observed
parasitemia in the treatment group could be almost wholly attributed to the measured
reinfection rate in this cohort. This method has been reported previously in comparing
the efficacy of antimalarial drug regimens (13,14).
Measures of Risk of Malaria 21
3.2.8. Attributable Fraction
Attributable fraction represents an estimate of the risk of disease in a community
that is attributable to a particular risk factor. Because many symptoms of malaria are
non-specific, attributable fraction is a useful measure in looking at clinical markers or
case definitions for malaria in a community. The statistic assigns a probability of a
single fever episode being due to malaria. For a single exposure variable, the overall
attributable fraction is given by
AF = p(R – 1)/R
where p is the exposure prevalence among cases and R is the relative risk of disease
associated with the exposure (15). The probability that any individual case is attribut-
able to malaria is calculated without multiplying by p (16).
Probabilities derived from logistic regression models can increase the precision of
the attributable fraction estimates by allowing fever risk as a continuous function of
parasite density (16) and can be further extended to include other covariates (17).
Schellenberg et al. (18) used the fraction of fever cases in a population attributable
to malaria at each level of parasite density to evaluate the sensitivity and specificity of
alternative case definitions for malaria, and to provide a direct estimate of malaria-
attributable fever. The attributable fraction statistic also has been used to determine the
specificity and sensitivity of case-definition thresholds (19).
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P. berghei
Life Cycle 25
25
From:
Methods in Molecular Medicine, Vol. 72: Malaria Methods and Protocols
Edited by: Denise L. Doolan © Humana Press, Inc., Totowa, NJ
3
Maintenance of the
Plasmodium berghei
Life Cycle
Robert E. Sinden, Geoff A. Butcher, and A. L. Beetsma
1. Introduction

Plasmodium berghei was probably first described in 1946 by Vincke in blood films
of the stomach contents of Anopheles dureni. In 1948, it was subsequently found in
blood films of Grammomys surdaster collected in Kisanga, Katanga; blood was pas-
saged to white rats and became the K173 strain made widely available by the Institute
for Tropical Medicine in Antwerp. A trio of fascinating papers describing the discov-
ery and early analysis of the biology of P. berghei (1–3) give an early indication of the
natural and catholic host range of this parasite (Table 1), a property that possibly
underlies the successful transmission of the parasite to a variety of laboratory hosts.
Although the natural vector of P. berghei is A. dureni, early laboratory studies (3,4)
showed that a wide range of colonized mosquitoes would successfully transmit the
parasite (Table 2).
Since their introduction to the laboratory, rodent malarias have made an enormous
contribution to our understanding of the biology, cell biology, and immunology of the
malaria parasites (5). A search of the more recent literature available on electronic
databases indicates that there are 10,617 publications on P. falciparum, compared to
2655 on P. berghei, 413 on P. chabaudi, and 152 on P. vinckei.
Notwithstanding this large knowledge base, other important factors currently con-
tributing to the enormous potential of research on rodent malarias, and P. berghei in
particular, include the following:
1. The wide availability of susceptible, genetically defined or knockout mouse strains.
2. An extensive range of well-characterized clones of P. berghei, some with important bio-
logical phenotypes, e.g., an inability to produce mature sexual-stage parasites.
3. The facility to make and analyze in vivo-defined gene knockouts in this parasite species
currently surpasses that in other Plasmodium species (e.g., P. falciparum and P. knowlesi).
4. The parasite can be transmitted through major vector species from Africa, India, and South
America (see Table 2).
5. Infections can readily be synchronized.
6. All the life cycle stages can be grown in vitro, thus permitting direct comparison of in vivo
and in vitro data.
7. The genome is now being analyzed, and expressed sequence tags (EST) and gene sequence

survey (GSS) databases are under construction.
26 Sinden et al.
2. Materials
2.1. Anesthetics for Rodents
When it is not important whether the host-body temperature falls, for example, for the
routine blood-feeding of stock mosquitoes, the anesthetics Nembutal or Saggatal (60 mg/mL
pentobarbitone sodium [BP]; Rhone Meriuex) are very satisfactory. For mice, rats or
rabbits, 0.125 mL Saggatal per100 g body weight is a routine dose and is administered
intraperitoneally. However, animals rapidly accommodate to these anesthetics. Alterna-
tively, for invasive procedures, rats may be anesthetized with halothane–oxygen.
Table 1
List of Natural and Laboratory Hosts of
P. berghei
Natural hosts Laboratory hosts
Muridae
Thamnomys surdaster Brown Norway rat (<4 wk)
Praomys jacksoni White rat (<4 wk)
Leggada belle Mouse
Saccotomus campestris Thamnomys surdaster
Mastomys coucha Grammamys rutilans
Æthomys sp. Ondatra zibethica (musk rat)
Pelomys frater Hamster (good for gametocytes)
Lophyromys aquilus
Crocidura turba
Sciuridae
Unnamed
Carnassieridae?
Unnamed
See refs. 1–3.
Table 2

Vectorial Capacity of Mosquitoes for P.berghei
Vector Nonvector
Anopheles dureni (1) Culex bitaeneorhynchus (1)
A. stephensi (1) (var mysorensis) Aedes aegypti (1,2)
a
A. gambiae (1) Anopheles albimanus (1)
A. atroparvus (1) A. aztecus (1)
A. quadrumaculotus (1) A. concolor (1)
A. maculipennis (2) A. coustani (1) var ziemanni
A. albimanus (3) A. fluviatilis (1)
A. funestus (1)
A. hyrcanus (1)
A. jamesi (1)
A. pulcherrimus (1)
A. splendidus (1)
A. subpictus (1)
a
Produced oocysts (SP28 strain S. Keiberg) (see refs. 3 and 4, and M C.
Rodriguez, personal communication).
P. berghei
Life Cycle 27
For mice, we prefer to use a mixture of Rompun™ (2-(2,6-xylidino)-5,6-dihydro-4H-
1,3-thiazine hydrochloride, 2% stock solution; Bayer), and Vetalar™ (100 mg/mL
ketamine; Parke-Davis)—both kept at 4°C. In a sterile tube, mix 1 vol of Rompun with 2 vol
of Vetalar and 3 vol of sterile phosphate-buffered saline (PBS). This will keep at 4°C for
up to 2 wk without loss of activity. Use this diluted mixture at 0.05 mL/10 g body weight.
Deliver intramuscularly into the thigh; there may be local bleeding, the animal may be-
come transitorily hyperactive, but thereafter anesthesia is deep and thus suitable for car-
diac bleeds or for exposure to mosquitoes. Anesthesia may persist up to 45 min.
2.2. Phenylhydrazine for the Induction of Reticulocytosis

Prepare a sterile stock solution of 1.2 mg/mL phenylhydrazine (phenylhydrazinium
chloride; BDH 10189) in PBS. Use at a rate of 10 µL/g body weight, inoculated intra-
peritoneally to induce reticulocytosis in mice. Inoculation should be 3 d before infec-
tion of the host by blood transfer.
2.3. Heparin Anticoagulant
Prepare a stock solution of 1 mg/mL (ca. 300 U/mL) preservative-free heparin
(Sigma 9133) in PBS. Use at a nominal final dilution of 1:10 in blood.
2.4. Giemsa Staining of Blood Films
Dilute concentrated Giemsa stain (BDH R66) to 20% or 10% in buffer (0.7 g anhy-
drous KH
2
PO
4
plus 1.0 g anhydrous Na
2
HPO
4
per liter distilled H
2
O). Stain air-dried,
methanol-fixed cells for 10 or 45 min, respectively, rinse very briefly in tap water or
buffer, and air-dry.
2.5. Fructose/PABA Feed for Mosquitoes
Combine 8 g fructose and 0.05 g p-aminobenzoic acid (PABA). Make up to 100 mL
in distilled water. Filter-sterilize, or autoclave. Store at 4°C.
2.6. Membrane Feeders
2.6.1. Feeder Sources
1. Discovery Workshops, 516A Burnley Road, Accrington, Lancashire BB5 6JZ, UK; e-
mail: Volume: 1 mL. Has an integral electrical heater.
2. Department of Aeronautics, Imperial College. Volume: 1 mL. Perspex construction with

demountable feeder units. Requires a circulating water bath.
3. All-glass feeders following design of Wade are available from various sources (e.g.,
Bioquip Products, 17803 LaSalle Avenue, Gardena, CA 90248-3602).
2.6.2. Membranes
1. For the majority of cases, 2-way stretch Parafilm-M available from Merck Ltd. (Merck
House, Poole, Dorset BH15 1TD, UK) is perfectly satisfactory.
2. For the fastidious mosquito (or experimenter), Baudruche membrane is available from
John Long, New Jersey.
2.7. Mercurochrome Staining of Oocysts
Prepare a 1% solution of mercurochrome (BDH-Merck 29177-4Y) in PBS; this can
be stored for 1 mo at 4°C. To prolong the observation time of stained oocysts on mid-
28 Sinden et al.
guts, postfix in 1% formaldehyde or 1% glutaraldehyde. The two solutions can be mixed
if required, but the guts become more resistant to flattening under pressure of the cover
slip, and as a consequence, the observation of the gut wall is often more difficult.
2.8. Fixation and Staining of Exoerythrocytic Stage Cultures
Rinse cultures in multiwell slides or on coverslips briefly in PBS and fix in Bouin’s
Fixative (85 mL of saturated picric acid, 10 mL of 40% formaldehyde, 5 mL of acetic
acid) for 10–30 min. Then stain cultures in 10% Giemsa stain (see Subheading 2.4.)
overnight. Wash briefly in Giemsa buffer, then treat with 60% acetone in water to
enhance differentiation, then for 20 s each in 100% acetone, Histoclear R, and Euparal
essence. Mount preparations in Euparal Vert.
2.9. Culture Medium for HepG2 Cells and EE Cultures
HepG2 cells are available from a wide range of sources including ATCC (Rockville,
MD) and the European Collection of Cell Cultures (CAMR, Porton Down, Salisbury,
Wilt., SP4 OJ6, UK). Although some authors have suggested subclone HepG2 A16 is a
preferred option, we have found no differences in the susceptibility of this cell line
from a variety of sources. Stock cells are maintained in 25-cm
2
plastic Falcon flasks in

minimal essential medium (MEM) supplemented with 10% fetal calf serum (FCS),
50 µg/mL penicillin, 100 µg/mL streptomycin, 50 µg/mL neomycin, 1 mM
L-glutamine,
and nonessential amino acids (1× Flow mixture). Maintain cells at 37°C in 5% CO
2
in
air. For subculture, inoculate trypsinized stock cultures at 1 × 10
5
cells per well onto
cover slips in 4-well or 24-well Nunc tissue culture plates, or Lab-Tek 8-chamber sides.
When near confluence, irradiate the cells at 3–3.5 krad from a cobalt-60 source.
2.10. Blood-Stage Culture Medium
Dissolve 10.41 g of RPMI 1640 powder (Sigma, Poole, Dorset, UK) in 960 mL
deionized water, and add 5.94 g of HEPES. Check that pH is 7.4. Sterilize by filtration
and store for up to 4 wk at –20°C. Immediately before use, add 4.2 mL of sterile 5%
NaHCO
3
solution, 11 mL of FCS, and 5.5 mg neomycin to 96 mL medium.
2.11. Ookinete Culture Medium
Dissolve powdered RPM1 1640 medium (Sigma R 4130) containing 0.025 M
HEPES in 900 mL deionized water. Add 0.05 g of hypoxanthine, 2 g of NaHCO
3
,
50,000 IU penicillin, and 50 mg streptomycin, and make up to 1 L final volume. Adjust
pH to 8.3 with 1 M NaOH. Then add either FCS to a final concentration of 20%, or (less
satisfactorily) add Ultroser-G (Gibco) to a final concentration of 0.4%. Store complete
medium in appropriate volumes at –20°C.
2.12. Purification of Asexual Stages
2.12.1. Equipment
1. Slides.

2. Scissors, forceps.
3. 10- to 50-mL syringes.
4. 1-mL syringes.
5. Needles (26-gage 1/2, 0,45 × 13).
6. Nylon wool.
P. berghei
Life Cycle 29
2.12.2. Reagents
1. Mice (strain not critical).
2. P. berghei clone 2.33.
3. Phenylhydrazine-HCl.
4. Rompun™/Vetelar™/PBS.
5. Heparin (300 U/mL).
6. 70% Ethanol.
7. Blood-stage culture medium (see Subheading 2.10.).
8. Whatman CF11 cellulose powder.
9. Nycodenz (Nycomed Pharma AS, Oslo, Norway).
10. PBS.
2.13. Purification of Schizonts
2.13.1. Equipment
1. Slides.
2. Scissors, forceps.
3. 10- to 50-mL syringes.
4. 1-mL syringes.
5. Needles (26G A1/2, 0,45 × 13).
6. Nylon wool.
2.13.2. Reagents
1. Wistar rat (180–250 g).
2. P. berghei clone 2.34 or 2.33.
3. Phenylhydrazine-HCl.

4. Rompun/Vetelar/PBS.
5. Heparin (300 U/mL).
6. 70% Ethanol.
7. Blood-stage culture medium (see Subheading 2.10.).
8. Whatman CF11 cellulose powder.
9. Nycodenz (Nycomed Pharma AS).
10. PBS.
2.14. Purification of Asexual-Free Gametocytes
2.14.1. Equipment
1. Slides.
2. Scissors, forceps.
3. 10- to 50-mL syringes.
4. 1-mL syringes.
5. Needles (26-gage A1/2, 0,45 × 13).
6. Nylon wool.
2.14.2. Reagents
1. Theilers Original (TO) mice.
2. P. berghei clone 2.34.
3. Phenylhydrazine-HCl.
4. Rompun/Vetelar/PBS.
5. Heparin (300 U/mL).