Assessing Long-Lasting Insecticidal Net Coverage, Access, and Utilization: Insights from Malaria-Endemic Regions and Rohingya Camps in Bangladesh

Assessing Long-Lasting Insecticidal Net Coverage, Access, and Utilization: Insights from Malaria-Endemic Regions and Rohingya Camps in Bangladesh | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Assessing Long-Lasting Insecticidal Net Coverage, Access, and Utilization: Insights from Malaria-Endemic Regions and Rohingya Camps in Bangladesh View ORCID Profile Mohammad Sharif Hossain , Amit Kumer Neogi , Ching Swe Phru , Nur-E Naznin Ferdous , View ORCID Profile Anamul Hasan , Shayla Islam , Md Mushfiqur Rahman , Md Mosiqure Rahaman , Md Nazrul Islam , Shyamol Kumer Das , Abu Toha Md Rezuanul Haque Bhuiyan , Md. Nazmul Islam , Md. Akramul Islam , View ORCID Profile Mohammad Shafiul Alam doi: https://doi.org/10.1101/2025.04.17.25326007 Mohammad Sharif Hossain 1 Infectious Diseases Division, International Centre for Diarrhoeal Disease Research , Bangladesh (icddr,b), Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mohammad Sharif Hossain Amit Kumer Neogi 2 Bangladesh Rural Advancement Committee (BRAC) Health Programme, BRAC , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ching Swe Phru 1 Infectious Diseases Division, International Centre for Diarrhoeal Disease Research , Bangladesh (icddr,b), Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nur-E Naznin Ferdous 2 Bangladesh Rural Advancement Committee (BRAC) Health Programme, BRAC , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anamul Hasan 1 Infectious Diseases Division, International Centre for Diarrhoeal Disease Research , Bangladesh (icddr,b), Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anamul Hasan Shayla Islam 2 Bangladesh Rural Advancement Committee (BRAC) Health Programme, BRAC , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md Mushfiqur Rahman 3 Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare , Government of Bangladesh, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md Mosiqure Rahaman 3 Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare , Government of Bangladesh, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md Nazrul Islam 3 Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare , Government of Bangladesh, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shyamol Kumer Das 3 Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare , Government of Bangladesh, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abu Toha Md Rezuanul Haque Bhuiyan 4 Refugee Relief and Repatriation Commissioner, Ministry of Disaster Management and Relief, Government of the People’s Republic of Bangladesh , Cox’s Bazar, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md. Nazmul Islam 3 Directorate General of Health Services (DGHS), Ministry of Health and Family Welfare , Government of Bangladesh, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Md. Akramul Islam 2 Bangladesh Rural Advancement Committee (BRAC) Health Programme, BRAC , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mohammad Shafiul Alam 1 Infectious Diseases Division, International Centre for Diarrhoeal Disease Research , Bangladesh (icddr,b), Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mohammad Shafiul Alam For correspondence: shafiul{at}icddrb.org Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Introduction Malaria remains a major public health challenge, particularly in endemic regions like Bangladesh. To combat this, the National Malaria Elimination Programme (NMEP) has been working to ensure long-lasting insecticidal nets (LLINs) reach vulnerable populations. This study assessed LLIN coverage, access, and utilization among the Bangladeshi population and Forcibly Displaced Myanmar Nationals (FDMN). Methods A cross-sectional survey was conducted from May to October 2023 across five malaria-endemic districts in Bangladesh and ten FDMN camps in Cox’s Bazar. Data were collected from 1,575 households using structured interviews. Statistical analyses were performed to evaluate LLIN distribution and utilization patterns among different demographic groups, particularly households with pregnant women and under-five children. Results Among Bangladeshi households, 97.6% owned at least one LLIN, with sufficient coverage for 93.2%. Utilization was high, with 96.4% sleeping under LLINs the previous night. Among pregnant women and under-five children, 95.0% and 98.3%, respectively, used LLINs. However, in FDMN households, while 98.2% owned at least one LLIN, only 44.3% had sufficient coverage, and utilization rates were significantly lower, with 65.7% sleeping under LLINs. Key barriers included inadequate LLIN supply. Conclusion Bangladesh has made significant progress in LLIN coverage and utilization among its population, surpassing WHO’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 five years has shown no change since 2015 ( 2 ). Bangladesh has developed a National Strategic Plan (NSP) for Malaria Elimination 2024-2030 that targets a malaria-free country by 2030, aligned with the “Global Technical Strategy for Malaria 2016-2030”. The goal of this plan is to, by 2027, attain zero mortality due to indigenous malaria and maintain this status and, by 2030, interrupt local transmission of indigenous malaria in a phased manner and prevent the re-establishment of local transmission ( 3 ). Among 64 districts, only 13 north-eastern and south-eastern 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 (CHT): Khagrachari, Rangamati, and Bandarban are considered as the hyper-endemic areas as they contributed to the majority of the cases ( 3 ). Plasmodium falciparum ( Pf ) is the most common malaria parasite in Bangladesh followed by Plasmodium vivax (Pv). The other two species, Plasmodium malariae (Pm) and Plasmodium ovale (Po), are rare. In 2023, the total number of malaria cases was reduced to 16,567 from 18,195 and deaths increased from 6 to 14 compared to 2022 ( 5 ). Of the total cases in 2023, only Pv alone accounted for 45.3% and this increase has been rapid like 5% in 2011 to 20.3% in 2020 and in 2022, it was 32.1% ( 6 , 7 ). 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 flocking to Bangladesh ( 8 ). In 2011, the United Nations Refugee Agency (UNHCR) reported that around 265,000 Rohingya were residing in Bangladesh and of them, 200,000 were undocumented by the Government of Bangladesh (GoB) 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 GoB in 13 malaria endemic districts since 2008 ( 12 ). Among the goals, two of them were: 1) to provide long-lasting insecticidal nets (LLINs) to 100% of households in the three malaria-endemic districts with the highest malaria burden and 80% coverage in the other ten malaria-endemic districts; 2) to 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 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 programme 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 & Communication (IEC) activities. Through a survey, it was also found that the net utilization percentage among pregnant women and children under five 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 utilization of LLINs in malaria-endemic areas of Bangladesh. On the other hand, in 2021, a small study was conducted to assess the coverage and utilization of LLINs among the FDMN. The study found very poor coverage and utilization in those areas ( 15 ). The objective of this study is to assess the coverage, access, and utilization of LLINs among the Bangladeshi people and to understand the perception of the Rohingya people regarding the 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 are NMEP’s concern about how people in the malaria endemic areas are accepting LLIN in their daily practice, whether the recipient households are using and caring for this in the appropriate manner, especially for the ethnic minorities, pregnant women, under-5 children in CHT, Non-CHT and FDMN areas. Study Area The cross-sectional survey unfolded in two phases: 1) encompassing five malaria-endemic districts of Bangladesh, consider five malaria endemic districts and distribution strategy of LLIN coverage and 2) spanning 10 Rohingya camps in FDMN, 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 households with children under 5 years of age or pregnant women, resulting in the final selection of 39 villages for data collection ( Fig 1 ). Download figure Open in new tab Fig 1. Study flow chart for sampling technique among Bangladeshi nationalities. 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 households during a single visit. During that visit, we asked the head or an adult member of the selected household 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 households in Bangladeshi community had LLINs. Thus, we expected that at least 95% of households 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 households needed to be surveyed. Information was collected from 25 households in each village, and therefore, a total sample of 75×39=975 households was included in the study. In FDMN areas, a study was conducted on a smaller scale in 2021 ( 15 ) and found that the household ownership of having LLINs was very low, only 68%. Thus, by considering that 70% of households were using LLINs and assuming a design effect 4% and a 5% statistical level of significance, minimum total of 505 samples would be required for this study. Considering a 10% refusal as well, a total of 556 households needed to be surveyed. A total of 600 households (on average 60 households from each camp) were interviewed from these 10 camps through the Probability proportional to size (PPS) sampling method ( Table 1 ) . View this table: View inline View popup Download powerpoint Table 1. FDMN population study area for LLIN survey. Data collection tools and techniques Data were collected between May and October 2023 through face-to-face interviews with the household heads or the representatives of the household using a pre-tested structured questionnaire ( S1 File ). Besides socio-demographic and household economy data, the questionnaire included information on the knowledge and practice of the household on different aspects of malaria, availability and use of LLINs especially by vulnerable groups (e.g., under-five children and pregnant women), knowledge of means of using insecticidal bed nets, and compliance with 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 (ODK) software version 2021.4.0 on the Android platform. To ensure data quality, a pre-designed data-check program implemented in STATA was utilized to identify inconsistencies. Statistical analyses were performed using the Stata software, version 15.1 (Stata Corporation, College Station, Texas, 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 t-tests were employed to compare quantitative variables between the two groups, while 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 both Bangla and English version of the consent form in accordance with the regulations of the Refugee Relief and Repatriation Commissioner (RRRC). Before obtaining any study-related information, the written informed consent was secured from all participants in presence of 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 prior informed written consent. The study information linked to participant identification was kept strictly confidential and inaccessible without due permissions. Result A total of 1,575household were interviewed and among them 61.9% were from Bangladeshi population and 38.1% were from FDMN ( Table 2 ) . Among the Bangladeshi respondents, only 13.9% were household head whereas 44.8% were in FDMN. Of the Bangladeshi respondents, 85.0% were female,and the median age was 28 years (inter-quartile range: 24 – 35 years), but among the FDMN, 66.5% were female, and the median age was 32 years (inter-quartile range: 26–42 years). A majority of FDMN household heads (63.5%) were unemployed, while the highest portion of Bangladeshi household heads were daily laborer (24.9%). View this table: View inline View popup Table 2. Demographic Characteristics of the study population. Regarding the LLIN coverage, in the CHT region, a small percentage of participants (1.6%) had no LLIN, while the majority had 3-4 bed-nets (48.3%), while in the Non-CHT region, a slightly larger proportion (4.0%) had no LLIN, with the majority having 55.6% with 1-2 bed-nets. Regarding the sufficiency of LLINs, in the CHT regions, 95.5% of households had sufficient LLINs, and in Non-CHT regions, it was 87.9% of LLINs. However, 98.2% of FDMN households had LLINs, with 93.0% having 1-2 bed-nets, but the sufficient number of LLINs was only 44.3% ( Table 3 ) . View this table: View inline View popup Table 3: Coverage of LLINs in the study areas of Bangladesh The findings from this survey indicate that, on average, there was approximately one LLIN for every 2 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 WHO. In contrast, in Non-CHT areas, this proportion was 2.3 (752 LLINs for 1711 persons) ( Fig 2 ). Download figure Open in new tab Fig 2. Rate of population per LLIN in the study area. Overall, more than 93% of Bangladeshi respondents indicated that all of their household members were able to sleep under LLINs; however, it was 93.1% and 92.4% among households with under-five-year-old children and pregnant women, respectively. In contrast, in FDMN, 41.4% reported that all of their household members were able to sleep under the LLINs, and among households with under-five-year-old children and pregnant women, only 45.3% and 43.0%, respectively were able to do so. While asking the reasons why all household 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 FDMN. The primary reasons cited for household members sleeping under the LLIN every night in both regions was “Fear of mosquito bites” (66.6% in Bangladeshi population and 91.8% in FDMN).When asked the reason why household members do not sleep under the LLIN every night in both the Bangladeshi(98.8%) and FDMN(86.9%) regions, the primary reason was “Inadequate number of LLINs” ( Table 4 ) . View this table: View inline View popup Table 4. Accessibility of LLINs in the household in the study area Of the total population, 96.4% slept under LLINs the night before the survey, whereas in FDMN, it was only 65.7%. When comparing the study area (CHT) with non-CHT areas, 97.3% and 94.4% of participants, respectively, used LLINs in the CHT and non-CHT areas. The difference between the two areas is statistically significant ( p -value < 0.001). Among the pregnant women and children under the age of five, 95.0% and 98.3%, respectively, slept under LLINs the previous night of the survey, while in FDMN, this percentage was 77.4% and 78.3%, respectively ( Table 5 ). View this table: View inline View popup Download powerpoint Table 5. Utilization of LLINs the previous night of the survey in study area Discussion The indicators of LLIN coverage in the high and low endemic area of Bangladesh and in the area of FDMN were investigated in this study. In total, 97.6% of the households among the Bangladeshi population and 98.2% had at least one LLIN in their household. Compared to the previous study among the Bangladeshi population in this region, reported LLIN coverage is significantly higher ( 16 ) but almost similar to another study ( 17 ), indicating ongoing efforts by the government and other NGOs to combat malaria realigned with the national strategy to ensure that 100% of households 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 – 23 ). As recommended by the WHO, the objective is to guarantee one LLIN for every two household members in order 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 household members in the malaria hyper-endemic areas. However, the general coverage was one for every two household 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 households that received LLINs, 93.2% reported that every family member was able to sleep under the LLIN each night. The fact that so many households in the area owned LLINs shows how important mass-distribution efforts were for making sure that people who lived in places where malaria was common own LLINs. This access rate was much higher compared with the study conducted in Thailand (86.1%) ( 27 ), Ethiopia (88.9%) ( 28 ) and Nigeria (33.0%) ( 29 ). The proportion of all the family member could be able to sleep under the LLINs of the household having at least one under five years of children was 98.3% and among households having at least one pregnant woman, it was 95.0%. While in FDMN, the percentage was very low (41.4%).However, among the household having at least one child under five 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 LLIN the night prior to the interview which was much higher compared with previous study ( 13 ), and much higher than the WHO’s recommended optimal threshold (80%) ( 31 ). The utilization rate was superior in comparison to 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 in order to control morbidity and mortality due to malaria, particularly in high per-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 compared with 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 five years of age in this study among the Bangladeshi population was 98.3%. The utilization of LLINs among children under five 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 utilization in FDMN was fairly low (65.7%), but higher compared with India ( 18 ) and Ethiopia ( 28 ). The proportions of utilization among the pregnant women (77.4%) and children under five 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, utilization, and malaria incidence, as it captures only a snapshot of the situation during data collection. Moreover, while disparities in LLIN access and utilization 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, while 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 utilization 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 usage. Public health initiatives must tackle these complex challenges to improve the effectiveness of LLIN programs and support the overarching objective of malaria prevention. Supporting information S1 File. The structured questionnaire. S1 Checklist. The STROBE statement checklist for cross sectional study Author Contributions Conceptualization, M.S.H., A.K.N., N.-E.N.F. and M.S.A.; methodology, M.S.H., A.K.N, C.W.P, N.-E.N.F. and M.S.A.; software, M.S.H.; validation, M.S.H., A.K.N. and N.-E.N.F.; formal analysis, M.S.H. and M.S.A.; investigation, 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; data curation, M.S.H., A.K.N., C.W.P. and N.-E.N.F.; writing—original draft preparation, M.S.H. and M.S.A.; writing—review and editing, 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.; visualisation, M.S.H. and A.H.; supervision, 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.; funding acquisition, M.S.H., M.A.I. and M.S.A. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by The Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) through BRAC (Grant number GR-01959). 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: 16 April 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.) if requested reasonably. Conflicts of Interest The authors declare no conflict of interest. Acknowledgments We express our gratitude to all the individuals who participated in this study and to the dedicated personnel involved. 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