Malaria prevalence in endemic districts of Bangladesh.

Abstract

Following the 1971 ban of DDT in Bangladesh, malaria cases have increased steadily. Malaria persists as a major health problem in the thirteen south-eastern and north-eastern districts of Bangladesh. At present the national malaria control program, largely supported by the Global Fund for AIDS, Tuberculosis and Malaria (GFATM), provides interventions including advocacy at community level, Insecticide Treated Net (ITN) distribution, introduction of Rapid Diagnostic Tests (RDT) and combination therapy with Coartem. It is imperative, therefore, that baseline data on malaria prevalence and other malaria indicators are collected to assess the effectiveness of the interventions and rationalize the prevention and control efforts. The objective of this study was to obtain this baseline on the prevalence of malaria and bed net use in the thirteen malaria endemic districts of Bangladesh.
In 2007, BRAC and ICDDR,B carried out a malaria prevalence survey in thirteen malaria endemic districts of Bangladesh. A multi-stage cluster sampling technique was used and 9750 blood samples were collected. Rapid Diagnostic Tests (RDT) were used for the diagnosis of malaria. The weighted average malaria prevalence in the thirteen endemic districts was 3.97%. In five south-eastern districts weighted average malaria prevalence rate was 6.00% and in the eight north-eastern districts weighted average malaria prevalence rate was (0.40%). The highest malaria prevalence was observed in Khagrachari district. The majority of the cases (90.18%) were P. falciparum infections. Malaria morbidity rates in five south-eastern districts was 2.94%. In eight north-eastern districts, morbidity was 0.07%.
Bangladesh has hypoendemic malaria with P. falciparum the dominant parasite species. The malaria situation in the five north-eastern districts of Bangladesh in particular warrants urgent attention. Detailed maps of the baseline malaria prevalence and summaries of the data collected are provided along with the survey results in full, in a supplemental information.

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Malaria Prevalence in Endemic Districts of Bangladesh
Ubydul Haque1, Syed Masud Ahmed2, Shahed Hossain1, Mamun Huda1, Awlad Hossain2, Mohammad
Shafiul Alam1, Dinesh Mondal1, Wasif Ali Khan1, Mohammod Khalequzzaman1, Rashidul Haque1*
1International Center for Diarrhoeal Disease Research Bangladesh, Mohakhali, Dhaka, Bangladesh, 2BRAC, BRAC Centre, Dhaka, Bangladesh
Abstract
Background: Following the 1971 ban of DDT in Bangladesh, malaria cases have increased steadily. Malaria persists as a
major health problem in the thirteen south-eastern and north-eastern districts of Bangladesh. At present the national
malaria control program, largely supported by the Global Fund for AIDS, Tuberculosis and Malaria (GFATM), provides
interventions including advocacy at community level, Insecticide Treated Net (ITN) distribution, introduction of Rapid
Diagnostic Tests (RDT) and combination therapy with Coartem. It is imperative, therefore, that baseline data on malaria
prevalence and other malaria indicators are collected to assess the effectiveness of the interventions and rationalize the
prevention and control efforts. The objective of this study was to obtain this baseline on the prevalence of malaria and bed
net use in the thirteen malaria endemic districts of Bangladesh.
Methods and Principal Findings: In 2007, BRAC and ICDDR,B carried out a malaria prevalence survey in thirteen malaria
endemic districts of Bangladesh. A multi-stage cluster sampling technique was used and 9750 blood samples were
collected. Rapid Diagnostic Tests (RDT) were used for the diagnosis of malaria. The weighted average malaria prevalence in
the thirteen endemic districts was 3.97%. In five south-eastern districts weighted average malaria prevalence rate was 6.00%
and in the eight north-eastern districts weighted average malaria prevalence rate was (0.40%). The highest malaria
prevalence was observed in Khagrachari district. The majority of the cases (90.18%) were P. falciparum infections. Malaria
morbidity rates in five south-eastern districts was 2.94%. In eight north-eastern districts, morbidity was 0.07%.
Conclusion and Significance: Bangladesh has hypoendemic malaria with P. falciparum the dominant parasite species. The
malaria situation in the five north-eastern districts of Bangladesh in particular warrants urgent attention. Detailed maps of
the baseline malaria prevalence and summaries of the data collected are provided along with the survey results in full, in a
supplemental information
Citation: Haque U, Ahmed SM, Hossain S, Huda M, Hossain A, et al. (2009) Malaria Prevalence in Endemic Districts of Bangladesh. PLoS ONE 4(8): e6737.
doi:10.1371/journal.pone.0006737
Editor: Simon I. Hay, University of Oxford, United Kingdom
Received May 6, 2009; Accepted June 19, 2009; Published August 25, 2009
Copyright: ? 2009 Haque et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was implemented with Global Fund for AIDS TB and Malaria (GFATM) support. The project was jointly implemented by BRAC (BRAC is a
brand name and it can’t be expanded) and ICDDR,B (International center for diarrhoeal disease research Bangladesh). The funders had no role in study design,
data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: rhaque@icddrb.org
Introduction
Malaria is estimated to be directly responsible for around one
million deaths annually worldwide [1]. The morbidity and
mortality burden caused by malaria are responsible for nearly
3% of the world’s DALYs [2]. Even though Africa accounts for
90% of the mortality burden for malaria, South-east Asia still
suffers considerable mortality and morbidity. Malaria is a major
public health problem in Bangladesh. Of the 11 countries of the
World Health Organization South East Asian Regional Office, ten
countries including Bangladesh are malaria endemic.
Due to the frequent use of DDT by the Malaria Eradication
program of the then Government of East Pakistan, malaria was
mostly under control before 1971 [3]. After the independence of
Bangladesh from Pakistan, DDT was banned in 1985 and the
number of malaria cases began to increase. Since the incidence of
malaria in the eastern regions was low and there was a lack of
adequate funds and programs, no control efforts maintained in the
malaria endemic areas of Bangladesh. Without these control
efforts, malaria cases started to increase and became epidemic in
the 1990s [3,4]. In the late 1990s, more than 500 deaths were
reported with 70,000 laboratory-confirmed cases and 900,000
clinical cases of malaria in Bangladesh [5].
The number of malaria cases in Bangladesh fluctuates
seasonally. The majority of these cases occur in the thirteen
districts close to and/or bordering India and Myanmar. These
thirteen districts, out of the 64 administrative districts of
Bangladesh, are recognized as malaria endemic. Ninety eight
percent of the malaria case reports come from these thirteen
districts. Three out of these thirteen districts, Bandarban,
Khagrachari and Rangamati, collectively known as the Chitta-
gong Hill Tracts (CHT) districts, report the highest incidence of
malaria within the country. These thirteen districts are difficult to
reach due to the hilly terrain and therefore have inadequate
passive surveillance and information systems resulting in poor
reporting of malaria cases by the Ministry of Health, Government
of Bangladesh [6,7].
In 2006, the Global Fund for AIDS, TB and Malaria
(GFATM), awarded Bangladesh USD 39.6 million to support
the national malaria control program. These funds were used by
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the national malaria control program to start advocacy at
community level, ITN distribution, introduction of rapid diagnosis
test (RDT) and to introduce combined therapy with coartem. In
the absence of baseline information, these resources could not be
equitably distributed among the population. Furthermore, these
data would be needed for future comparisons to assess the
effectiveness of these programs. Therefore in 2007, BRAC and
ICDDR,B carried out this first ever malaria prevalence survey of
Bangladesh, the results of which are presented here.
Methods
Objectives
Our primary objective was to assess the prevalence of malaria in
thirteen malaria endemic districts of Bangladesh. In addition to
the prevalence survey, we investigated the use of bednets in
endemic regions.
Study Area
The research was carried out in seventy Thanas (sub districts) of
thirteen malaria endemic districts of Bangladesh. According to the
Ministry of Health, Government of Bangladesh, 98% of the cases
are reported from these Thanas of Bangladesh [8]. These thirteen
districts are divided into two parts. Eight north-eastern districts
share a common border with India. Five south-eastern districts
situated in the south-eastern part of Bangladesh. Three of these
districts share the common border with India and Myanmar and
are known as Chittagong Hill Tracts (CHT) Districts. These three
districts area is mostly hilly, forested and thus relatively
inaccessible.
Sample size calculation
We anticipated the malaria prevalence in our eight north-
eastern endemic districts to be around 2%, while in the five south-
eastern endemic districts it would be more than 3%. Given the
design of the study as a cluster survey, the sample size had to
incorporate these expectations [10]. The sample size was
calculated using web-based software C-Survey 2.0 based on the
conservative estimates of malaria prevalence and the design effect.
Sample size was estimated assuming the lowest estimate of malaria
prevalence at 2% with a precision of 1.5%, at 95% confidence
interval with a design effect of two. Thus, 750 individuals from 750
households were taken in each district for this study. Totally 9,750
individual samples from thirteen malaria endemic districts were
collected for this study.
Sampling
A three stage cluster sampling technique was employed using
population figures from the 2001 census. City Corporations and
towns were excluded from this survey because they are urban and
of extremely low malaria risk. For each of the thirteen districts, all
Mauzas (Mauzas are the lowest administrative unit of Bangladesh,
bigger than village and have a polygon boundary) were listed
alphabetically and 30 Mauzas were selected using a probability
proportional to size (PPS) sampling procedure [11]. These Mauzas
were the primary sampling unit of the survey. Twenty-five
households were selected using systematic randomization from
each Mauzas/cluster (Figure 1). All population in a cluster was
eligible to participate in the survey. Information about bed net use
was obtained from the head or spouse (or a knowledgeable
member in their absence) of the selected household. For
prevalence (parasitological) survey, one household member from
each household was randomly chosen.
Ethical considerations
The protocol was reviewed and approved by the research
review committee and the ethical review committee of ICDDR,B.
The probability and magnitude of harm or discomfort anticipated
in the proposed research are not greater in and of themselves than
those ordinarily encountered in daily life or during the
performance of routine physical, psychological examinations or
tests. The study is therefore expected to be minimal risk. Written
consent was obtained from the participants.
Recruitment, training and deployment of the
interviewers
The survey team comprised of experienced interviewers and
their supervisors. A five-day intensive training was organized for
the interviewers consisted of didactic lectures, mock interviews,
role play and field practice at community level. Each team
typically consisted of four members including one person trained
in malaria microscopy. The training was organized by the experts
from BRAC and ICDDR,B prior to the start of the survey.
Field operation
The malaria prevalence survey was conducted during Septem-
ber, October and November 2007. In each of the selected mauza
(‘‘clusters’’), the study team drew a map. The field team selected
households systematically, as they moved from the center or
periphery, following a designated path determined by the ‘‘spin
the bottle’’ methodology [11].
All members of the household were listed. Only one individual
from a household was enrolled into this study using a simple
randomisation procedure. Informed consent was obtained before
proceeding with the survey activities. Selected individuals were
tested for malaria and information collected for any febrile illness
in the past 15 days. One team member drew four drops of finger
prick blood from each participant. Rapid Diagnostic test (RDT)
for malaria was performed on the spot. We also kept one note in
our record whether he/she suffered with fever within last 15 days
or not. If he/she suffered with fever, we recorded that morbidity.
Patients diagnosed as having malaria were provided Coartem for
treatment. A socioeconomic survey related to malarial knowledge
and relevant health-seeking behavior was also conducted. A semi-
Figure 1. Shows study procedure and sampling.
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Figure 2. Shows the survey cluster locations.
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structured questionnaire was developed and use for this purpose,
the results of which will be presented elsewhere.
Diagnosis of Malaria
Malaria was diagnosed by Rapid Diagnostic Tests (RDT) that
detects both P. falciparum-specific antigen and Plasmodium vivax-
specific antigen. The trade name of this RDT is ‘‘FalciVax’’ and is
produced by Zephyr Biomedicals, India (www.tulipgroup.com).
Each FalciVax is rapid self-performing, qualitative, two site
sandwich immunoassay utilizing whole blood for the detection of
P. falciparum specific histidine rich protein-2 (Pf, HRP-2) and P.
vivax specific pLDH. The test can be used for specific detection and
differentiation of P. falciparum and P. vivax malaria. The
standardization of this test has already been done by the Zephyr
Biomedicals. Sensitivity of the RDT is similar to that commonly
achieved by good field microscopy. Sensitivity and specificity of
the RDT used for the detection of P. falciparum and P. vivax is more
than 95% and now been recommended for use in the malaria
control program by the World Health Organization [12,13,14].
GPS data collections
The coordinates (longitude and latitude) of all selected Mauzas
(n=390) were recorded on-site using eTrex Venture Garmin
single handheld GPS receivers. GPS points were uploaded to a
Fox Pro database system and checked for accuracy at the field
level. GPS points were superimposed on the polygon boundary
and verified accuracy. Arc GIS 9.2 software was used for
developing map. Figure 2 shows the exact cluster locations from
where blood samples were collected.
Data preparation and statistical analysis
An anonymous database was created and double checked. Fox
Pro was used for data entry and storage. Data was cleaned and
checked for duplicates. District, Thana, Union, Mauza, household
and person identifier was given and later converted into a unique
identifier. Of the 9750 questionnaire obtained, one questionnaire
about bed nets was lost and 9749 questionnaires were used for
analysis. Descriptive summaries of infection prevalence were
generated using STATA 10 and MS Excel 2007. To account for
the clustered nature of the data, the svy command in STATA was
used with the cluster as the primary sampling unit (psu) stratified by
District. All results were weighted (weight=1/probability of
selection) to account for unequal probabilities of selection of
clusters across District. To test for differences in proportion of
participant livelihood (categorized as south-eastern and north-
eastern district), bed-net using status in their house (bed-net related
variable is listed as a binary variable with their mean as the cut-off
point) between malaria positive and malaria negative household a
Pearson chi-square test according to survey design (cluster and
stratification) was used and the test statistic converted to an F-
statistic using the second-order Rao and Sott correction yielding
wider confidence intervals and conservative P-value compared to
the uncorrected Chi-square test. To find the independent risk
factors for malaria positive households, a logistic regression
analysis were performed. Variables with a p value ,=0.05 level
in the bivariate analysis (converted F-statistic) were included in a
stepwise logistic regression procedure.
Results
In thirteen malaria endemic districts, the overall weighted
malaria prevalence rate was 3.97% (Table 1). The survey clusters
(see supplemental information file) and malaria prevalence maps
were prepared (figure 2, 3 and 4 respectively). Figure two shows
the survey cluster locations. The distribution of P. falciparum is
presented in figure three. Plasmodium falciparum was found in
eleven districts of the thirteen surveyed districts. The prevalence
rate varied from 0.13% to 15.07%. Figure four, shows that P. vivax
was found in ten districts; in which the prevalence rate varied
from 0.13 to 1.2%. The weighted prevalence of P. falciparum was
3.58% and the P. vivax 0.21% and mixed infection with P.
falciparum and P. vivax was 0.18%. The proportion of P. falciparum
was 90.18% while P. vivax and mixed infection with these two
species were 5.29 and 4.53% respectively in these thirteen
districts. Prevalence of P. falciparum in males and females was
3.96% and 3.98% respectively. The prevalence of malaria was
significantly higher in children. The prevalence of falciparum
malaria in children 0–4 years of age was 8.5% and 5–14 years of
age 6.6%. P. vivax prevalence among male are 0.15%, and female
Table 1. Overall and age, sex and area wise prevalence of different Malaria parasite infection (Weighted).
Prevalence
Any (pf or pv) infectionPf infectionPv infection Mixed (pf and pv) infection
% [95% CI]% [95% CI] % [95% CI] % [95% CI]
Over all3.97 [3.11–4.83]3.58 [2.75–4.42]0.21 [0.08–0.34]0.18 [0.01–0.35]
By sex
Male 3.96 [2.96–4.97]3.60 [2.67–4.54] 0.15 [0.01–0.29]0.21 [21.1–0.53]
Female 3.98 [2.89–5.08] 3.57 [2.50–4.64]0.27 [0.06–0.48]0.15 [0.03–0.27]
By age group
0–4 yrs11.34 [6.83–15.9] 10.32 [5.98–14.7]0.63 [20.03–1.28]0.40 [20.26–1.05]
5–14 yrs8.69 [6.06–11.32]8.35 [5.75–10.94] 0.21 [20.04–0.46] 0.13 [20.02–0.28]
15–49 yrs 2.74 [2.06–3.42]2.42 [1.77–3.07]0.19 [0.02–0.37] 0.13 [0.01–0.25]
.=50 yrs1.84 [0.89–2.80]1.30 [0.58–2.03] 0.17 [20.07–0.43] 0.36 [20.24–0.96]
By area/districts
South-eastern6.00 [4.67–7.34] 5.49 [4.18–6.79] 0.31 [0.11–0.49] 0.21 [20.05–0.50]
North-eastern 0.40 [0.19–0.63]0.25 [0.01–0.41]0.04 [20.04–0.12]0.11 [0.02–0.21]
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Figure 3. Distribution of Plasmodium falciparum in endemic areas of Bangladesh. The distribution of P. falciparum is presented in Figure 3.
Plasmodium falciparum was found in eleven districts of the thirteen surveyed districts. The prevalence rate varied from 0.13% to 15.07%.
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Figure 4. Distribution of Plasmodium vivax in endemic areas of Bangladesh. Figure four, shows that P. vivax was found in ten districts; in
which the prevalence rate varied from 0.13 to 1.2%.
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are 0.27%. Mixed infection prevalence among male and female
were 0.21% and 0.15% respectively. In five south-eastern districts
the average weighted prevalence rate was 6.00% while in the eight
north -eastern districts average weighted prevalence rate was
0.40%. The overall malaria prevalence in Chittagong Hill Tracts
(CHT) districts was 11.7%. The prevalence rate was 15.25%,
10.97% and 7.42% in Khagrachari, Bandarban and Rangamati
districts respectively.
When we conducted the survey, we randomly identified one
person and performed a RDT. We recorded whether this
individual reported fever within last fifteen days. If he/she had
suffered with fever within last fifteen days and was RDT positive,
we considered that is morbid event. Malaria morbidity was found
to be higher in the five south-eastern districts when compared to
the eight north-eastern districts.
A total of 9750 participants in the study area, 300 were RDT
positive and 9450 were negative. Please see the supplemental
information (Table S1). Households of RDT positive participants
were considered as malaria infected households and RDT negative
participant’s households are malaria non-infected households.
Bednet use information of 9749 participants was used for statistical
analysis and only one participant’s information was missing. About
91.1% (n=267) and 93.7% (8799) participant’s households had a
bed net among the malaria positive and negative households
respectively (p=0.118, not significant). We have also observed that
the bed net use pattern in the infected and non-infected
households and found that malaria infected households having
significantly less number of bednets (,=2) compared to malaria
non-infected households (Table 2). It was also found that
significantly more malaria infected households are in the five
south-eastern districts compared malaria non-infected households
(Table 2). In the five south-eastern districts the percentage of bed
nets treated with medicine within last six months were similar for
both types of households. Table 3 shows the adjusted odds ratios
(OR) for the variables using the logistic regression model.
Independent risk factors for malaria infection found significant
in multivariate analysis for the entire surveyed area when less than
or equal to two bednets in household (OR=1.87, 95% CI=1.30–
2.71) and households in south-eastern districts (OR=17.31, 95%
CI=9.60–31.30).
Table 2. Bed net use pattern as well as participants districts by malaria infected and non-infected households (HH).
Malaria infected HH Malaria non-infected HHP-value
N=300N=9449
%(95% CI)n% (95%CI)N
Bed net status in participant house
Having bed net 91.1 (86.6–94.2)26793.7(92.6–94.6)8799 0.118
Having ,=2 bed nets57(49.1–64.6)198 46.4(44.4–48.3) 54610.006
,=5 family member use bed net regularly57.6 (50.0–65.0) 21455.2 (53.3–57.2)64870.529
Bed-net treated with medicine within last 6 month01.7 (0.64–5.50) 0502(1.3–2.8) 1630.885
Last night bed-net use by
All family member80.3(73.2–86.0) 239 83.8(82.0–85.4) 79170.274
,=3 adults members68.1 (61.6–73.9)23261.4 (59.2–63.5)6653 0.044
,=2 child members57.4(48.9–65.5) 20662.2(59.7–64.6)6690 0.255
,=2 male members 53.3(46.7–60.0) 19146.8 (45.3–48.4)54240.054
,=2 female members50.5 (43.9–57.2)18951.8 (50.1–53.6)5853 0.885
Participants districts
South-eastern96.3(93.5–98.0)271 62.4(61.7–63.0)3480
,0.0001
North-eastern03.7 (02.1–06.5)2937.7 (37.0–38.3)5969
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Table 3. Significant independent risk factors associated with malaria infection: adjusted OR with 95% CI as estimated by logistic
regression.
Malaria infected HH (N=300)Malaria non-infected HH (N=9449) Adjusted OR (95% CI)P- value
Bed net in housenn
,=2 bed-net 19854611.87(1.30–2.71)0.001
.2 bed-net202 42881.00
Participants districts
South-eastern district 2713480 17.31(9.60–31.30)
,0.0001
North-eastern district 29 59691.00
Bed net in house 19854611.87(1.30–2.71) 0.001
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Discussion
In order to implement an effective malaria control program in
Bangladesh, accurate information on the incidence and prevalence
of malaria is required. In this study, the first malaria prevalence
survey was conducted to provide the baseline parasitological
information for population living in the malaria endemic districts
of Bangladesh. This cross-sectional survey provides point preva-
lence data on malaria in these thirteen malaria endemic districts.
These data will also be a massive help of global initiatives of
malaria mapping [15].
We have found a much higher prevalence of malaria than
would be expected by investigating the national passive surveil-
lance information [16]. This indicates that by the passive
surveillance conducted by the national malaria control program
significantly underestimates the burden of malaria in these 13
malaria endemic districts, especially in the five south-eastern
districts.
Given that no significant difference was found between male
and female malaria prevalence rates, it can be concluded that the
gender difference will not be an issue for malaria control.
However, there were significantly higher rates of infection among
children, thus indentifying a need for targeted interventions for
young populations.
Malaria is not equally distributed in all malaria endemic districts
of Bangladesh. Prevalence of malaria in five south-eastern districts
is significantly higher than the eight north-eastern districts.
Chittagong Hill Tracts (CHT) districts have the highest prevalence
than the other endemic districts. The reason might be that CHT
districts are hilly and covered with forest and lakes, provide an
excellent habitat for malaria vectors [17]. Resources should be
differentially targeted to this area given its larger malaria burden.
The combined use of GIS (geographic information system) and
remote sensing provides a significant tool to control malaria [18].
We hope GIS and high resolution satellite images can be used to
detect malaria hot spots and vectors habitat sites, particularly in
CHT districts, as part of our ongoing work.
From this study it is also clear that P. falciparum is the dominant
species in the malaria endemic districts of Bangladesh, with the
highest prevalence occurring in the CHT districts. This is of high
concern since P. falciparum is known to be the most deadly and
drug resistance for treatment of P. falciparum is a worldwide
problem [19]. Risk factors regarding the use of bed nets in this
study have been found to be consistent with similar studies
conducted in Somalia [20]. This study also confirms the results
obtained in Vietnam that the households having two or more than
two bednets are more protective [21]. The use of two or more than
two bednets in a household is an effective malaria control
intervention in Bangladesh. Efforts should be focused to increase
the supply of at least two bednets in the malaria endemic areas of
Bangladesh, especially in the south-eastern districts of Bangladesh.
Total population in endemic areas are 26.9 million, and the risk
exposure is as high as in many African countries [22,23].
Longitudinal studies are needed to assess the variation of
asymptomatic parasite carriage over time, and its exact contribu-
tion to transmission. Population-based prevalence studies on a
regular basis are required to understand the burden of disease.
More studies should be conducted in the future to map the
changing malaria epidemiology in Bangladesh as control activities
are scaled up.
Limitations
The main limitation of the survey was we failed to start the
survey in thirteen districts synchronously. The first the survey
started in south eastern part and as soon as we finished, we moved
to north eastern part. So, work in the north eastern part was not
done during malaria peak season. Any future work mapping the
distribution of prevalence in Bangladesh will have to consider this
fact in the modelling.
Supporting Information
Table S1
Found at: doi:10.1371/journal.pone.0006737.s001 (0.13 MB
XLS)
Acknowledgments
We are grateful for all field staff for collecting data.
Author Contributions
Conceived and designed the experiments: UH SMA SH AH MSA DM
WAK MK RH. Analyzed the data: UH MH. Contributed reagents/
materials/analysis tools: UH RH. Wrote the paper: UH. Edited the initial
versions of manuscript: SH DM RH. Principal investigator of the project:
RH.
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