Highlights
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Most Bangladeshi families regularly use mosquito nets, even for children.
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Rohingya households own nets but lack enough, especially for vulnerable groups.
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The main reason for not using nets is the shortage in both population groups.
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Bangladesh exceeds bed net targets, but refugee camps are falling behind.
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Refugee areas need better net supply to meet malaria goals by 2030.
Keywords: Malaria, LLIN, FDMN, Plasmodium, Bangladesh
Abstract
Objectives
Malaria remains a major public health challenge, particularly, in endemic regions such as Bangladesh. To combat this, the National Malaria Elimination Programme has been working to ensure that long-lasting insecticidal nets (LLINs) reach vulnerable populations. This study assessed LLIN coverage, access, and use among the Bangladeshi population and forcibly displaced Myanmar nationals (FDMNs).
Methods
A cross-sectional survey was conducted from May to October 2023 across five malaria-endemic districts in Bangladesh and 10 FDMN camps in Cox’s Bazar. Data were collected from 1575 households (HHs) using structured interviews. Statistical analyses were performed to evaluate LLIN distribution and use patterns among different demographic groups, particularly, HHs with pregnant women and children aged under 5 years.
Results
Among Bangladeshi HHs, 97.6% owned at least one LLIN, with sufficient coverage for 93.2%. The use rate was high, with 96.4% sleeping under LLINs the previous night. Among pregnant women and children aged under 5 years, 95.0% and 98.3%, respectively, used LLINs. However, in FDMN HHs, although 98.2% owned at least one LLIN, only 44.3% had sufficient coverage, and use rates were significantly lower, with 65.7% sleeping under LLINs. Key barriers included inadequate LLIN supply.
Conclusions
Bangladesh has made significant progress in LLIN coverage and use among its population, surpassing World Health Organization’s 80% threshold. However, gaps remain in the FDMN population, necessitating targeted interventions to achieve universal coverage and further reduce malaria morbidity and mortality.
Introduction
Among the mosquito-borne diseases, malaria is the oldest one that causes many clinical symptoms such as a sensation of cold, fever, chills, headaches, nausea, vomiting, sweating, joint pain, prostration, and malaise [1]. The World Malaria Report 2023 claimed an estimated 249 million malaria cases in 2022 in 84 malaria-endemic countries, which was a 5 million increase from 2021. Apart from the cases, the estimated number of deaths decreased from 631,000 in 2019 to 608,000 in 2022. However, the percentage of total malaria deaths in children under 5 years has shown no change since 2015 [2].
Bangladesh has developed a National Strategic Plan for Malaria Elimination 2024-2030 that targets a malaria-free country by 2030, aligned with the “Global Technical Strategy for Malaria 2016-2030.” The goals of this plan are to attain zero mortality due to indigenous malaria by 2027and maintain this status and interrupt local transmission of indigenous malaria in a phased manner and prevent the re-establishment of local transmission by 2030 [3]. Among 64 districts, only 13 northeastern and southeastern districts of Bangladesh bordering India and/or Myanmar are malaria-endemic [4]. An estimated 17.7 million people are at risk of malaria in those endemic areas. Based on the annual malaria incidence, three districts of the Chattogram hill tracts (CHTs)—Khagrachari, Rangamati, and Bandarban—are considered as the hyper-endemic areas because they contributed to the majority of the cases [3]. Plasmodium falciparum is the most common malaria parasite in Bangladesh, followed by Plasmodium vivax. The other two species, Plasmodium malariae (Pm) and Plasmodium ovale (Po), are rare. However, P. ovale is composed of two species: P. ovale wallikeri and P. ovale curtisi [5]. In 2023, the total number of malaria cases was reduced to 16,567 from 18,195 and deaths increased from six to 14 compared with 2022 [6]. Of the total cases in 2023, only P. vivax accounted for 45.3%, and this increase has been rapid, 5% in 2011 to 20.3% in 2020, and in 2022, it was 32.1% [7,8].
In 1978, Myanmar imposed the Emergency Immigration Act under the military regime on the minority Muslim Rohingyas, which started the Rohingya crisis and led to the Muslim Rohingyas migrating to Bangladesh [9]. In 2011, the United Nations High Commissioner for Refugees reported that around 265,000 Rohingya were residing in Bangladesh, and, of them, 200,000 were undocumented by the Government of Bangladesh and other non-governmental organizations (NGOs) [9]. On August 25, 2017, Myanmar started an exodus in Rakhine State and as a result, more than 712,179 sought asylum in Bangladesh [10]. By October 2019, an estimated 911,566 Rohingya refugees were seeking asylum in the Cox’s Bazar district of Bangladesh [11]. Almost all of them reside in 34 camps of Cox’s Bazar which is also a malaria-endemic area. In 2022, a total of 65 malaria cases were detected and it rose to 94 in 2023, and between January and June of 2024, the number reached 244.
The National Malaria Elimination Programme (NMEP), together with the NGO consortium led by BRAC, has achieved remarkable success in malaria control through continuous support from the Global Funds to Fight AIDS, Tuberculosis and Malaria (GFATM) and the Government of Bangladesh in 13 malaria-endemic districts since 2008 [12]. Among the goals, two of them were (i) to provide long-lasting insecticidal nets (LLINs) to 100% of households (HHs) in the three malaria-endemic districts with the highest malaria burden and 80% coverage in the other 10 malaria-endemic districts and (ii) provide periodic (every 3 years) treatment of non-LLINs with suitable insecticides [12]. Between July 2021 and June 2024, a total of 350,000 LLINs was distributed among the forcibly displaced Myanmar nationals (FDMN) population at risk through mass campaigns.
BRAC and International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) jointly conducted the first-ever malaria prevalence survey of Bangladesh in 2007 [13], followed by a follow-up survey in 2013 supported by NMEP [4]. From these surveys, it was found that the use of the insecticidal bed nets significantly increased in 2013 compared with 2007. Since 2007, the BRAC-led consortium of 20 smaller partner NGOs has been working on a malaria control and prevention program through insecticidal bed net distribution; early diagnosis and management; providing treatment according to the national guideline; referral of complicated cases to the nearest district hospital for better management; and information, education, and communication activities. Through a survey, it was also found that the net use percentage among pregnant women and children aged under 5 years was 85% and 90%, respectively [14]. However, to keep track of the program’s performance, the survey of the use of insecticidal bed nets (LLIN/ITNs) needs to be done annually.
To track the success of the program, from 2008 and onward, a regular survey has been conducted to estimate the use of LLINs in malaria-endemic areas of Bangladesh. On the other hand, in 2021, a small study was conducted to assess the coverage and use of LLINs among the FDMNs. The study found very poor coverage and use in those areas [15]. This study aimed to assess the coverage, access, and use of LLINs among the Bangladeshi people and understand the perception of the Rohingya people regarding LLIN use in FDMN camp areas.
Materials and methods
Study design
Aligned with the study objectives, this cross-sectional study will measure the coverage of LLINs, which is the NMEP’s concern about how people in the malaria-endemic areas are accepting LLINs in their daily practice and whether the recipient HHs are using and caring for these in the appropriate manner, especially for the ethnic minorities, pregnant women, children aged under 5 years in CHT, non-CHT, and FDMN areas.
Study area
The cross-sectional survey unfolded in two phases: (i) encompassing five malaria-endemic districts of Bangladesh, considering five malaria-endemic districts and distribution strategy of LLIN coverage and (ii) spanning 10 Rohingya camps in FDMNs, Cox’s Bazar. Of the five selected districts, three are hyper-endemic districts (Khagrachari, Rangamati, and Bandarban) and the other two are low malaria-endemic districts (Cox’s Bazar and Chattogram). We randomly selected three upazilas from each of the Khagrachari, Rangamati, and Bandarban districts and two upazilas from each of the Cox’s Bazar and Chattogram districts. Thus, in total, 13 upazilas were included in this study. From each upazila, three villages were selected randomly from the list of the villages where LLINs had been distributed by NMEP to HHs with children aged under 5 years or pregnant women, resulting in the final selection of 39 villages for data collection (Figure 1).
Figure 1.
Study flow chart for sampling technique among Bangladeshi nationalities.
CHT, Chattogram hill tract; HH, household.
In FDMN areas, the LLINs were distributed across 34 camps at the onset of the crisis in 2018. From these 34 camps, we randomly selected 10 for the LLIN cross-sectional survey. Again, in a village or camp, data were collected from HHs during a single visit. During that visit, we asked the head or an adult member of the selected HH whether they were interested in participating in this study. If interested, they were asked to provide the written informed consent and then were enrolled in the study.
Sample size
Previous study found that [15] the overall (90.9%) (CHT: 99.3% and Non-CHT: 72.0%) of HHs in Bangladeshi community had LLINs. Thus, we expected that at least 95% of HHs would be using LLINs. Assuming the difference between the estimated and true prevalence (i.e. the design effect of 1.5% and 5% statistical level of significance), a minimum total of 811 samples would be required for this study. Considering a 10% refusal rate to provide the information, at least a total of 893 HHs needed to be surveyed. Information was collected from 25 HHs in each village, and, therefore, a total sample of 75 × 39 = 975 HHs was included in the study.
In FDMN areas, a study was conducted on a smaller scale in 2021 [15] and found that the HH ownership of having LLINs was very low, only 68%. Thus, by considering that 70% of HHs were using LLINs and assuming a design effect 4% and a 5% statistical level of significance, a minimum total of 505 samples would be required for this study. Considering a 10% refusal as well, a total of 556 HHs needed to be surveyed. A total of 600 HHs (on average, 60 HHs from each camp) were interviewed from these 10 camps through the probability proportional to size sampling method (Table 1).
Table 1.
Forcibly displaced Myanmar nationals population study area for long-lasting insecticidal net survey.
| Upazila | Name of the areas | Number of camps | Total HH | Targeted HH | HH surveyed |
|---|---|---|---|---|---|
| Ukhiya | Kutupalong | Two extension | 6650 | 67 | 67 |
| Kutupalong Registered Camps | 3242 | 32 | 32 | ||
| 4 | 8194 | 82 | 82 | ||
| 7 | 8345 | 84 | 84 | ||
| Balukhali | 9 | 7808 | 78 | 78 | |
| Palongkhali | 15 | 13750 | 138 | 138 | |
| 21 | 3614 | 24 | 24 | ||
| Teknaf | Leda | 24 | 7616 | 47 | 47 |
| 27 | 3579 | 33 | 33 | ||
| Nayapara Registered Camp | 3705 | 15 | 15 |
HH, household.
Data collection tools and techniques
Data were collected between May 10, 2023 and October 25, 2023 through face-to-face interviews with the HH heads or the representatives of the HH using a pre-tested structured questionnaire (See Additional file 1). In addition to socio-demographic and HH economy data, the questionnaire included information on the knowledge and practice of the HH on different aspects of malaria, availability and use of LLINs (especially by vulnerable groups, e.g. children aged under 5 years and pregnant women), knowledge of means of using insecticidal bed nets, and adherence to treatment. Data were collected in tabs and transferred in real-time to the online server whenever available.
Statistical analysis
Data entry into the tabs was conducted using Open Data Kit software version 2021.4.0 on the Android platform. To ensure data quality, a pre-designed data check program implemented in STATA was used to identify inconsistencies. Statistical analyses were performed using the Stata software, version 15.1 (Stata Corporation, College Station, TX, USA).
Baseline characteristics for two groups, CHT and non-CHT, were analyzed using summary statistics, including the number, mean, median, inter-quartile range, standard deviation, minimum, and maximum. Unpaired Student’s t-tests were used to compare quantitative variables between the two groups, whereas categorical variables were assessed using either the chi-square test or Fisher’s exact test. Proportions between groups were compared using Z-statistics. A significance level of P <0.05 was considered statistically significant in all analyses.
Informed consent
To ensure accurate translation of the consent forms into the local language, a comprehensive forward-and-backward translation process was implemented. However, in FDMN areas, we adhered to the Bangla and English version of the consent form in accordance with the regulations of the Refugee Relief and Repatriation Commissioner. Before obtaining any study-related information, written informed consent was secured from all participants in the presence of a local interpreter, known as Majhi.
The consent process involved providing participants with detailed information about the study’s objectives, the nature of the data collected, potential benefits and risks, and a guarantee of confidentiality for all information and results generated by the study. The information and consent form were verbally communicated to all participants, with illiterate individuals expressing their consent through a fingerprint in the presence of a witness.
Participants were explicitly informed of their right to withdraw their consent at any point during the interview without the obligation to provide a reason or fear any negative consequences.
Ethical approval
This study was conducted after obtaining formal approval (PR-20097) from the Ethical Review Committee of icddr,b, Mohakhali, Dhaka. No participants were interviewed without obtaining informed written consent. The study information linked to participant identification was kept strictly confidential and inaccessible without due permissions.
Result
A total of 1575 HHs were interviewed, and, among them, 61.9% were from the Bangladeshi population and 38.1% were from FDMNs (Table 2). Among the Bangladeshi respondents, only 13.9% were HH heads, whereas 44.8% were FDMNs. Of the Bangladeshi respondents, 85.0% were female and the median age was 28 years (inter-quartile range: 24-35 years); however, among the FDMNs, 66.5% were female and the median age was 32 years (inter-quartile range: 26-42 years). A majority of FDMN HH heads (63.5%) were unemployed, whereas the highest portion of Bangladeshi HH heads were daily laborers (24.9%).
Table 2.
Demographic characteristics of the study population.
| Characteristics | Bangladeshi respondents, N = 975; n (%) |
Forcibly displaced Myanmar national respondents, N = 600; n (%) |
|---|---|---|
| Type of the respondent | ||
| HH head | 135 (13.9) | 269 (44.8) |
| Spouse of HH head | 686 (70.4) | 276 (46.0) |
| Other | 154 (15.8) | 55 (9.2) |
| Sex | ||
| Male | 146 (15.0) | 201 (33.5) |
| Female | 829 (85.0) | 399 (66.5) |
| Age, years | ||
| Median (interquartile range) | 28 (24-35) | 32 (26-42) |
| Education | ||
| No schooling | 193 (19.8) | 414 (69.0) |
| 1-5 Years | 302 (31.0) | 126 (21.0) |
| 6-9 Years | 283 (29.0) | 41 (6.8) |
| 10-12 Years | 178 (18.3) | 12 (2.0) |
| Graduate | 14 (1.4) | 4 (0.7) |
| Other | 5 (0.5) | 3 (0.5) |
| Occupation of HH head | ||
| Agriculture | 188 (19.3) | 0 (0.0) |
| Jhum cultivation/rubber plantation | 79 (8.1) | 0 (0.0) |
| Unemployed | 0 (0.0) | 381 (63.5) |
| Own business | 150 (15.4) | 26 (4.3) |
| Rickshaw/van/boat/car driver | 144 (14.8) | 13 (2.2) |
| Carpenter/Mason | 243 (24.9) | 119 (19.8) |
| Daily labor | 107 (11.0) | 51 (8.5) |
| Service other | 64 (6.6) | 10 (1.7) |
| Family size | ||
| ≤4 | 353 (36.2) | 190 (31.7) |
| ≥5 | 622 (63.8) | 410 (68.3) |
HH, household.
Regarding the LLIN coverage, in the CHT region, a small percentage of participants (1.6%) had no LLINs, whereas the majority had 3-4 bed nets (48.3%), whereas in the non-CHT region, a slightly larger proportion (4.0%) had no LLINs, with the majority having 55.6%, with 1-2 bed nets. Regarding the sufficiency of LLINs, in the CHT regions, 95.5% of HHs had sufficient LLINs, and, in non-CHT regions, it was 87.9% of LLINs. However, 98.2% of FDMN HHs had LLINs, with 93.0% having 1-2 bed nets, but the sufficient number of LLINs was only 44.3% (Table 3).
Table 3.
Coverage of LLINs in the study areas of Bangladesh.
| Characteristics | Study area |
|||
|---|---|---|---|---|
| Bangladeshi |
Forcibly displaced Myanmar nationals | |||
| CHT (n = 675) | Non-CHT (n = 300) | Total (n = 975) | Total (n = 600) | |
| HHs have any LLINs? | ||||
| Yes No |
664 (98.4) 11 (1.6) |
288 (96.0) 12 (4.0) |
952 (97.6) 23 (2.4) |
589 (98.2) 11 (1.8) |
| How many LLINs? (among HHs that have LLINs) | ||||
| 1-2 bed nets 3-4 bed nets Five or more bed nets |
271 (40.1) 321 (48.3) 72 (10.8) |
160 (55.6) 105 (36.5) 23 (7.9) |
431 (45.3) 426 (44.8) 95 (9.9) |
548 (93.0) 39 (6.6) 2 (0.3) |
| HHs have sufficient LLINs? (among HHs that have LLINs) | ||||
| Yes No |
634 (95.5) 30 (4.5) |
253 (87.9) 35 (12.1) |
887 (93.2) 65 (6.8) |
261 (44.3) 328 (55.7) |
| How many LLINs are usable now (not ripped/ruined)? (among HHs that have LLINs) | ||||
| None 1-2 bed nets 3-4 bed nets Five or more bed nets |
28 (4.2) 292 (44.0) 300 (45.2) 44 (6.6) |
25 (8.7) 172 (59.7) 76 (26.4) 15 (5.2) |
53 (5.6) 464 (48.7) 376 (39.5) 59 (6.2) |
116 (19.7) 455 (77.2) 18 (3.1) 0 (0.0) |
| Where did you get the LLINs from? | ||||
| Global fund Another source Don’t know |
664 (100.0) 0 (0.0) 0 (0.0) |
288 (100.0) 0 (0.0) 0 (0.0) |
952 (100.0) 0 (0.0) 0 (0.0) |
322 (56.4) 64 (10.9) 193 (32.8) |
CHT, Chattogram hill tract; HH, household; LLIN, long-lasting insecticidal net.
The findings from this survey indicate that, on average, there was approximately one LLIN for every two people (2696 LLINs for 5249 persons), and, among the FDMN population, it was for every 3.9 person (875 LLINs for 3,419 persons). In CHT areas, the proportion of population per LLIN was 1.8 (1944 LLINs for 3538 persons), which is the target coverage by the World Health Organization (WHO). In contrast, in non-CHT areas, this proportion was 2.3 (752 LLINs for 1711 persons) (Figure 2).
Figure 2.
Rate of population per LLIN in the study area.
CHT, Chattogram hill tract; LLIN, long-lasting insecticidal net.
Overall, more than 93% of Bangladeshi respondents indicated that all their HH members were able to sleep under LLINs; however, it was 93.1% and 92.4% among HHs with children aged under 5 years and pregnant women, respectively. In contrast, among FDMNs, 41.4% reported that all their HH members were able to sleep under the LLINs, and, among HHs with children aged under 5 years and pregnant women, only 45.3% and 43.0%, respectively, were able to do so. Although asking the reasons why all HH members can’t sleep under the LLINs, the primary reason cited in both the regions was “inadequate number of LLINs” (98.5% in Bangladeshi population and 86.7% in FDMNs). The primary reasons cited for HH members sleeping under the LLIN every night in both regions was “fear of mosquito bites” (66.6% in Bangladeshi population and 91.8% in FDMNs).When asked the reason why HH members do not sleep under the LLIN every night in the Bangladeshi (98.8%) and FDMN (86.9%) regions, the primary reason was “inadequate number of LLINs” (Table 4).
Table 4.
Accessibility of LLINs in the HH in the study area.
| Characteristics | Study area |
|||
|---|---|---|---|---|
| Bangladeshi |
Forcibly displaced Myanmar nationals | |||
| CHT (n = 664) | Non-CHT (n = 288) | Total (n = 952) | Total (n = 600) | |
| All the HH members can sleep under the LLINs? | ||||
| Yes No |
634 (95.5) 30 (4.5) |
253 (87.9) 35 (12.1) |
887 (93.2) 65 (6.8) |
244 (41.4) 345 (58.6) |
| All the HH (HHs that had children under 5 years) members can sleep under the LLINs? | ||||
| Yes No |
594 (95.7) 27 (4.3) |
235 (87.4) 34 (12.6) |
829 (93.1) 61 (6.9) |
185 (45.3) 223 (54.7) |
| All the HH (HHs that had a pregnant woman) members can sleep under the LLINs? | ||||
| Yes No |
59 (95.2) 3 (4.8) |
38 (88.4) 5 (11.6) |
97 (92.4) 8 (7.6) |
37 (43.0) 49 (57.0) |
| Why can’t all the HH members sleep under the LLINs? | ||||
| Inadequate No. of LLINs LLIN is ripped Other |
30 (100.0) 0 (0.0) 0 (0.0) |
34 (97.1) 1 (2.9) 0 (0.0) |
64 (98.5) 1 (1.5) 0 (0.0) |
299 (86.7) 36 (10.4) 10 (2.9) |
| Does every member of your HH sleep under LLINs every night? | ||||
| Yes No Don’t know |
624 (94.0) 40 (6.0) (0.0) |
247 (85.8) 41 (14.2) (0.0) |
871 (91.5) 81 (8.5) (0.0) |
243 (41.3) 343 (58.2) 3 (0.5) |
| Reason why all the HH members sleep every night under LLINs | ||||
| Fear of malaria Fear of mosquito bits To stay free of disease Other |
105 (16.8) 420 (67.3) 99 (15.9) 0 (0.0) |
53 (21.5) 160 (64.8) 34 (13.8) 0 (0.0) |
158 (18.1) 580 (66.6) 133 (15.3) 0 (0.0) |
12 (4.9) 223 (91.8) 6 (2.5) 2 (0.8) |
| Reason why all the HH members do not sleep every night under the LLINs | ||||
| Inadequate number of LLIN LLIN is ripped Other |
40 (100.0) 0 (0.0) 0 (0.0) |
40 (97.6) 1 (2.4) 0 (0.0) |
80 (98.8) 1 (1.2) 0 (0.0) |
298 (86.9) 33 (9.6) 12 (3.5) |
CHT, Chattogram hill tract; HH, household; LLIN, long-lasting insecticidal net.
Of the total population, 96.4% slept under LLINs the night before the survey, whereas in FDMNs, it was only 65.7%. Comparing the study area (CHT) with non-CHT areas, 97.3% and 94.4% of participants used LLINs in the CHT and non-CHT areas, respectively. The difference between the two areas is statistically significant (P <0.001). Among the pregnant women and children under the age of 5 years, 95.0% and 98.3%, respectively, slept under LLINs the previous night of the survey, whereas in FDMNs, these percentages were 77.4% and 78.3%, respectively (Table 5).
Table 5.
Use of LLINs the previous night of the survey in the study area.
| Characteristicsa | Study area |
|||
|---|---|---|---|---|
| Bangladeshi |
Forcibly displaced Myanmar nationals | |||
| CHT % (n/N) |
Non-CHT % (n/N) |
Total % (n/N) |
Total % (n/N) |
|
| % Total population who slept under LLINs the previous night | 97.3 3263/3353 |
94.4 1489/1577 |
96.4 4752/4930 |
65.7 2126/3234 |
| % Children aged under 5 years who slept under at the previous night | 98.0 697/711 |
98.8 318/322 |
98.3 1015/1033 |
78.3 474/605 |
| % Pregnant women who slept under LLINs the previous night | 95.0 57/60 |
95.1 39/41 |
95.0 96/101 |
77.4 65/84 |
| % Males who slept under LLINs the previous night | 97.6 1573/1611 |
93.6 716/765 |
96.3 2289/2376 |
64.3 982/1526 |
| % Females who slept under LLINs the previous night | 97.0 1690/1742 |
95.2 773/812 |
96.4 2463/2554 |
67.0 1144/1708 |
CHT, Chattogram hill tract; HH, household; LLIN, long-lasting insecticidal net.
No. of individuals who slept last night under LLINs/No. of individuals present at the household last night.
Discussion
The indicators of LLIN coverage in the high and low endemic area of Bangladesh and in the area of FDMNs were investigated in this study. In total, 97.6% of the HHs among the Bangladeshi population and 98.2% had at least one LLIN in their HH. Compared with the previous study among the Bangladeshi population in this region, the reported LLIN coverage is significantly higher [16] but almost similar to another study [17], indicating that ongoing efforts by the government and other NGOs to combat malaria realigned with the national strategy to ensure that 100% of HHs in malaria hyper-endemic districts receive LLINs while also implementing targeted LLIN coverage in other malaria-endemic districts [12]. The proportion of LLIN/ITN coverage in both areas is similar to the neighboring country, India [18] and Myanmar [19], but higher than in Nepal [20] and some African countries [[21], [22], [23]]. As recommended by the WHO, the objective is to guarantee one LLIN for every two HH members to attain universal coverage [24], and the NMEP of Bangladesh has been very successful with the help of local NGOs lead by BRAC. The present study revealed that there was a supply of at least one LLIN for every 1.8 HH members in the malaria hyper-endemic areas. However, the general coverage was one for every two HH members and these findings were similar to Ethiopia [25] and Kenya [26]; nevertheless, the FDMN population has not yet met this benchmark.
The availability of LLINs was noted to be exceptional. Among the HHs that received LLINs, 93.2% reported that every family member was able to sleep under the LLIN each night. The fact that so many HHs in the area owned LLINs shows how important mass distribution efforts were in making sure that people who lived in places where malaria was common own LLINs. This access rate was much higher than in the study conducted in Thailand (86.1%) [27], Ethiopia (88.9%) [28], and Nigeria (33.0%) [29]. The proportion of all the family members that are able to sleep under the LLINs of the HHs having at least one child under 5 years was 98.3% and, among HHs having at least one pregnant woman, it was 95.0%. Although in FDMNs, the percentage was very low (41.4%). However, among the HHs having at least one child under 5 years of age and least one pregnant woman, the proportions were close to the levels recommended by the WHO [30].
The present study revealed that among the Bangladeshi population, 96.4% of total population slept under LLINs the night before the interview, which was much higher than previous study [13] and much higher than the WHO’s recommended optimal threshold (80%) [31]. The use rate was superior compared with other malaria-endemic regions, such as India (59.4%) [18], Nigeria (86.0%) [32], and Ethiopia (38.4%) [28]. It is crucial to ensure that the most vulnerable population are using ITN/LLINs extensively and regularly to control morbidity and mortality due to malaria, particularly, in hyper-endemic areas. This study also revealed that 95.0% Bangladeshi pregnant women slept under the LLINs in previous night of interview, which was much higher than other malaria-endemic regions, such as Burkina Faso (57.6%) [33], Madagascar (68.5%) [23], Ethiopia (79.1%) [34], Cameroon (82.5%) [35], and the bordering country, India (89.0%) [36]. This rate among the children under 5 years of age in this study among the Bangladeshi population was 98.3%. The use of LLINs among children under 5 in this area was comparable to that in India (96.0%) [36] but significantly greater than in other malaria-endemic countries, such as Madagascar (80.8%) [23], Nigeria (80.0%) [32], Liberia (39%) [37], and Kenya (59.0%) [38]. Moreover, the overall use in FDMNs was fairly low (65.7%) but higher than India [18] and Ethiopia [28]. The proportions of use among the pregnant women (77.4%) and children under 5 years of age (78.3%) were also low. The sleeping pattern between males (96.3%) and females (96.4%) was high and fairly similar among the Bangladeshi population, which was much higher than in India [18] and Rwanda [39].
Limitations
The limitations of this study are worth noting as well. The cross-sectional design limits the ability to establish causal relationships between LLIN coverage, use, and malaria incidence because it captures only a snapshot of the situation during data collection. Moreover, although disparities in LLIN access and use among the FDMN population were highlighted, the study did not explore the underlying sociocultural or logistical factors contributing to these gaps. Finally, the geographic coverage, although extensive, may not be entirely generalizable to other malaria-endemic areas of Bangladesh. Despite these limitations, the study provides valuable insights into LLIN coverage and use in Bangladesh.
Conclusion
In conclusion, these studies offer significant insights for the design and implementation of targeted malaria control interventions in Bangladesh. The findings highlight the necessity for strategies tailored to specific regions, considering demographic differences and variations in LLIN use. Public health initiatives must tackle these complex challenges to improve the effectiveness of LLIN programs and support the overarching objective of malaria prevention.
Declaration of competing interest
The authors have no competing interest to declare.
Acknowledgments
Funding
This research was funded by GFATM through BRAC (Grant number GR-01959).
Acknowledgments
The authors express their gratitude to all the individuals who participated in this study and the dedicated personnel involved. This research study was funded by BRAC through the GFATM. The icddr,b acknowledges with gratitude the commitment of BRAC and the GFATM to their research efforts. The icddr,b is also grateful to the Governments of Bangladesh and Canada for providing core/unrestricted support.
Author contributions
M.S.H., A.K.N., N.-E.N.F., and M.S.A. did the conceptualization; M.S.H., A.K.N, C.W.P, N.-E.N.F., and M.S.A. did the methodology; M.S.H. did the software work; M.S.H., A.K.N., and N.-E.N.F. did the validation part; M.S.H. and M.S.A. did formal analysis; M.S.H., A.K.N., C.W.P, N.-E.N.F., A.H., M.M.R. (Md. Mushfiqur Rahman), M.M.R. (Md. Musiqure Rahman), S.K.D., S.I., M.N.I., A.T.M.R.H.B, M.A.I., and M.S.A did the investigation; M.S.H., A.K.N., C.W.P., and N.-E.N.F. did data curation; M.S.H. and M.S.A. wrote the main manuscript; M.S.H., A.K.N., N.-E.N.F., C.W.P., A.H., S.I., M.M.R. (Md. Mushfiqur Rahman), M.M.R. (Md. Musiqure Rahman), M.N.I, S.K.D., A.T.M.R.H.B, M.N.I. (Md. Nazmul Islam), M.A.I., and M.S.A. reviewed and edited the manuscript; M.S.H. and A.H. did the visualization part; S.I., M.M.R. (Md. Mushfiqur Rahman), M.M.R. (Md. Musiqure Rahman), M.N.I, S.K.D., A.T.M.R.H.B, M.N.I. (Md. Nazmul Islam), M.A.I., and M.S.A. supervised the study; M.S.H., M.A.I., and M.S.A. did the funding acquisition. All authors have read and agreed to the published version of the manuscript.
Institutional review board statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the institutional review board of icddr,b (Protocol no: PR-20097 and date of approval: April 16, 2023).
Informed consent statement
Informed consent was obtained from all subjects involved in the study.
Data availability statement
The data presented in this study are available from the corresponding author (M.S.A.) upon reasonable request.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ijregi.2025.100715.
Appendix. Supplementary materials
Supporting information
Additional file 1. The structured questionnaire.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting information
Additional file 1. The structured questionnaire.
Data Availability Statement
The data presented in this study are available from the corresponding author (M.S.A.) upon reasonable request.