Malaria risk, treatment-seeking, and prevention in Northeastern India: Clinic-based surveillance of persistent transmission

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Wilson, Innang Lyngdoh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7138239/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Dec, 2025 Read the published version in Malaria Journal → Version 1 posted 9 You are reading this latest preprint version Abstract Background Malaria has historically been a public health concern in Meghalaya with year-round transmission peaking during the monsoon and post-monsoon seasons. This study investigated malaria prevalence among suspected cases presenting at health centres across three districts of Meghalaya, in the northeastern region (NER) of India. Methods A multi-site, facility-based, cross-sectional study was conducted in five primary health centres (PHC) and one district hospital from three geographically distinct regions of Meghalaya: West Khasi Hills [KH] district, West Jaintia Hills [JH] district, and South Garo Hills [GH] district. Individuals presenting at the selected healthcare facilities with malaria-like symptoms between 2018 and 2021 were enrolled. Malaria cases were detected by light microscopy, RDT, and PCR. Malaria prevalence was estimated as the number of Plasmodium infections divided by the total number of participants providing a blood sample. Logistic regression analysis was conducted to assess the risk factors of malaria. Results A total of 1,031 participants provided a blood sample for testing. Forty-five (4.4%) participants had a Plasmodium infection, most (60%) of which were P. falciparum . Malaria prevalence ranged from 1.8% in KH to 12.3% in GH. Diagnosis of malaria within the past 12 months (OR = 9.2; P < 0.001) and performing outdoor activities before bedtime (OR = 2.0; P = 0.023) or early morning (OR = 3.1; P = 0.010) were significantly associated with Plasmodium infection. Conclusion The results provide valuable insights into the epidemiology of malaria in an endemic region in NER of India. These findings emphasize the importance of considering specific local risk-factors, such as behavioural patterns, in designing effective malaria control strategies. Northeast India Malaria Prevalence Risk factors Plasmodium infection Figures Figure 1 Background Historically, malaria has been a public health concern in Meghalaya, a state in the northeastern region (NER) of India. Significant progress in controlling transmission has been achieved over the past decade, primarily due to targeted interventions, enhanced disease surveillance, and active community participation in use of preventive measures ( 1 ). The introduction of artemisinin-based antimalarial drugs for the treatment of malaria and widespread distribution of long-lasting insecticidal nets (LLINs) may have played a role in lowering malaria incidence, although other factors too may have played a role ( 1 , 2 ). For example, indoor residual spraying (IRS) has served as a complementary control method, though its coverage remains limited in certain areas ( 1 , 2 ). Malaria transmission in Meghalaya occurs year-round, with peak incidence during the monsoon season (May–July) ( 3 ). Travel history is a major risk factor, and individuals with prior malaria episodes also face a higher risk ( 4 ). Earlier community-based studies from Meghalaya have provided insights into malaria epidemiology, emphasizing the role of behavioural and environmental factors such as vector exposure and human mobility in malaria epidemiology ( 1 , 4 ). Despite these community-level findings, research on the clinical epidemiology of malaria in Meghalaya remains limited, with little attention given to patient-specific factors influencing malaria prevalence. Understanding these factors is crucial for refining malaria control strategies, identifying high-risk groups, and tracking disease trends. By analysing suspected malaria cases at the health centre level, valuable insights into disease burden and key risk factors can be obtained, helping to strengthen prevention, control, and the more recent move toward elimination ( 1 ). This facility-based surveillance investigated malaria prevalence among suspected cases presenting at government healthcare facilities in three districts of Meghalaya: West Jaintia Hills (JH), West Khasi Hills (KH), and South Garo Hills (GH). It also assessed the epidemiological patterns, risk factors, and health seeking behaviour of patients with malaria-like symptoms with the goal of helping policymakers and healthcare providers take data-driven decisions to strengthen India’s malaria elimination efforts. Methods Study design, area, and period Meghalaya is a mountainous, heavily forested state in Northeast India, bordered by the state of Assam in the north and the country of Bangladesh to the south ( 5 ). The population of Meghalaya is estimated to be over 3.5 million, representing predominantly tribal people mostly living in rural, forested settings ( 6 ). The economy is largely agrarian involving mixed farming. The climate is among the wettest in the world, especially during the rainy season ( e.g. , May-September). With temperatures ranging from 23-28 o C and high relative humidity (> 70%), the conditions are ideal for mosquito reproduction and perpetual transmission. The area’s major and minor transmission seasons take place between May-July and between September-November, respectively. While both P. falciparum and P. vivax are present across the state, P. falciparum is predominant in most regions ( 2 ). A multi-site, facility-based, cross-sectional study was conducted over a three-year period from September 2018 through November 2021 in three districts of Meghalaya. The facilities included: Nonglang Primary Health Centre (PHC) in West Khasi Hills district (KH), Barato PHC and Nartiang PHC in West Jaintia Hills (JH), and Rongara PHC, Siju PHC and Baghmara Civil Hospital in South Garo Hills (GH) (Fig. 1 ). Selection of the six health centres was based on state control programme Plasmodium infection records with the goal of capturing both high and low prevalence settings in the three districts. Ethical approval Approval to undertake the study was obtained from the Institutional Review Board at New York University, New York, NY, USA and the University Research Ethics Committee of Martin Luther Christian University, Shillong, Meghalaya, India. Written informed consent was obtained from all adult participants (≥ 18 years of age) and parental consent from participants aged <18 years. Additionally, assent was obtained from participants aged 7–17 years. Data and sample collection and analysis Socio-demographic and behavioural information was collected using a standardized questionnaire from individuals aged 1–69 years who presented to the health centres with malaria-like symptoms, which included fever, chills, sweating, headache, muscle aches, nausea, vomiting, or diarrhoea. Individual questionnaires were administered at the clinic to consenting participants or their parent/guardian (in case of children) in their native language ( e.g., Khasi, Pnar, Garo), to gather information on age, gender, education, occupation, knowledge of malaria, malaria episodes during previous year, fever episodes during previous 48 hours, travel history (past two weeks), and malaria prevention methods utilised. Questions on malaria-related risk behaviours and practices were also asked. Blood sample collection and Plasmodium detection Approximately 1 ml of blood was drawn via finger prick, and P . falciparum and/or P. vivax infections were detected at the point of care using both a bivalent rapid diagnostic test (RDT; FalciVax) and an ultra-sensitive RDT (Abbott Alere). Light microscopy evaluation of Giemsa-stained blood smears and PCR amplification of concentrated DNA extracted from microvette RBC pellets were also performed on all samples. Species-specific Plasmodium infections were detected using a single-step PCR targeting Pfr364 (for P. falciparum ) and Pvr47 (for P. vivax ) (7). Statistical analysis Subject data were collected by electronic data capture and stored in a secure, firewall protected REDCap (Research Electronic Data Capture) database (8). Data analysis was completed in Stata version 17 for Windows (StataCorp, College Station, Texas, USA). Analysis involved a complete-case approach, in which participants with missing data for important variables were eliminated. Summary statistics for continuous variables are presented as mean and standard deviation (SD), and as numbers and percentages (%) for categorical variables. The prevalence of malaria was estimated as the number of Plasmodium infections divided by the total number of participants from whom a sample was obtained. Associations between socio-demographic, environmental, or behavioural risk factors and Plasmodium infections were evaluated using logistic regression and reported as odds ratio (OR) with 95% confidence intervals (CI). Results Population sampled and Individual characteristics A total of 1,031 participants were enrolled across six PHCs surveyed in JH (n=722), KH (n=114), and GH (n=195) from September 2018 through November 2021. Blood samples were obtained and tested from all 1,031 participants. The mean (SD) age of participants was 24.1 (15.9) years. Overall, 54.2% of the study participants were female. Of the adult participants (≥18 years), 19.8% had no formal education. About half of all participants (51.3%) were engaged in agricultural-related activities. Malaria in the previous 12 months was reported by 8.2% of participants, while 9% reported a history of travel outside the village in the previous 14 days. About one in ten participants (11.6%) reported spending one or more nights in the field, with a mean (SD) of 5.8 (4.4) nights. Nearly one-quarter (23.5%) were engaged in ‘outdoor activities’ before 6 am. Nearly three-quarters (70.8%) reported using insecticide treated bed nets (ITNs) while staying in the field. Roughly one-third (34.6%) of all participants were familiar with the typical malarial signs and symptoms, which they reported as fever (94.9%), headache (71.9%), chills (78.3%), and body discomfort (54.3%). District level demographics and occupations The age and gender distributions of participants across the three districts are presented in Table 1, with males comprising between 43.1% and 55.3%. The proportion of adult participants with no formal education ranged from 11.2% to 63.4%. Between 6.9% and 77.5% of the participants were engaged in agricultural-related activities. 5.0% and 34.5% of the participants were housewives. Reported malaria diagnosis and risk behaviours In GH, 28.2% of participants (55/195) reported being diagnosed with malaria in the past 12 months, while the proportions were 10.5% (12/114) in KH and 2.4% (17/722) in JH (Table 1). A history of travel in the past 14 days was reported by 10.5% of the participants (76/722) in JH, 7.9% (9/114) in KH, and 4.1% (8/195) in GH. Staying overnight in the field for one or more days were reported by 16.5% (112/679) participants in JH, 4.2% (4/96) in KH, and 5.7% (4/70) in GH. The average (SD) number of days spent overnight in the field was 5.9 (4.5) days in JH, 3.5 (0.7) days in KH, and 4.0 (1.7) days in GH. Outdoor activities before 6 a.m. ‘wake-up’ time were reported by 68.6% (24/35) of participants in GH, 22.7% (55/251) in JH, and 6.8% (5/73) in KH. Knowledge of malaria signs and symptoms was reported by 69.7% (136/195) of participants in GH, 35.1% (40/114) in KH, and 25.1% (181/722) in JH. Health-seeking behaviour Nearly all respondents (97.2%) reported that a public healthcare facility ( i.e., primary health care centre or district hospital) is their first choice for seeking malaria treatment. If ineffective, 25.5% stated they would then seek care at a private clinic. This preference was reported regardless of whether the individual had previously experienced malaria. The proportion of respondents diagnosed with malaria who preferred to seek treatment from government healthcare facilities ranged from 83.3% to 100% across KH, GH, and JH. Reported malaria risk reduction Use of methods to prevent mosquito bites among participants was also analysed (Table 2). Almost all individuals (96.3%) reported using a bed net at night with virtually all reporting usage regularly (83.9%) or most of the time (11.4%). However, only 75.6% of the bed nets had been treated with insecticide. About half of respondents (55.8%) used clothing that covered their arms and legs to avoid mosquito bites, but 86.1% did not apply insecticide cream to prevent bites. Evening activities were reported by 95.5% of participants, which was usually held within the house. Virtually everyone ate their dinner (99.7%) and slept inside their houses. One quarter (24.5%) of activities recorded in the early morning occurred outside the house. Plasmodium infection prevalence Plasmodium infections were found by RDT and/or PCR and/or light microscopy in 4.4% (45/1,031) of individuals. Plasmodium infection was higher in GH (24/195, 12.3%) than in JH (19/722, 2.6%) and KH (2/114, 1.8%). Of the positives, 10 (22%) were positive by RDT only, 2 (4%) by PCR only, 14 (31%) by both RDT and PCR, 1 (2%) by both RDT and light microscopy, and 18 (40%) by all three methods ( e.g., RDT, PCR, and light microscopy); no infections were determined solely by microscopy. A slightly higher proportion of PCR-positive infections were reported from GH (18/34 ;40%) than from JH (15/34 ;33.3%) and KH (1/34 ;2%). Plasmodium falciparum was the only species detected in 60% (27/45) of positive samples, while 38% (17/45) were P. vivax , and 2% (1/45) were mixed ( P. vivax + P. falciparum ). Most of the P. vivax infections (17/19; 89.4%) were reported from JH. A case of malaria was defined as a positive Plasmodium infection based on RDT and/or PCR results. Risk factors for Plasmodium infection The factors associated with the risk of Plasmodium infection were assessed collectively and separately for the three districts (Table 3). Statistically significant increased risk was associated with reported history of malaria in the previous 12 months (OR=9.2, P <0.001), activity outside the house before bedtime (OR=2.0, P =0.023), and activity outside the house before 6 am (OR=3.1, P =0.010). None of the other factors assessed ( e.g., age, gender, education, occupation, IRS spraying, and LLIN use) were statistically significant. In GH, the odds of Plasmodium infection were significantly higher for individuals with a history of malaria in the past 12 months (OR=6.7, P < 0.001). Staying a night in the field (OR=19.0, P =0.015) and engaging in activities outside before bedtime (OR=4.8, P =0.018) were also significantly associated with increased odds of malaria in this district. In JH (OR=3.5, P =0.010) and (OR=2.3, P =0.547), younger people (<18 years) had significantly higher odds of Plasmodium infection this was not statistically significant in KH. Discussion This facility-based surveillance study investigated the prevalence and risk factors of Plasmodium infection among suspected malaria cases over a three-year period to gain deeper insights into the epidemiology of malaria in three districts of Meghalaya. The overall malaria prevalence among participants who were visiting health centres was 4.4%, consistent with a recent report analysing data from the National Vector Borne Disease Control Program (NVBDCP) (2) and findings from previous active, cross-sectional surveillance conducted in KH and JH (4). Collectively , these findings indicate a consistent decline in malaria cases in Meghalaya over the past decade . This decline can likely be attributed to the shift from sulphadoxine-pyrimethamine treatment to artemether-lumefantrine artemisinin combination therapy in 2013, and the state-wide distribution of LLINs in 2016, 2019 and 2020 (2,9,10). Additionally, advancements in diagnostic and treatment strategies, particularly the involvement of Accredited Social Health Activists (ASHAs) in testing and treating individuals with Plasmodium infections at the community level, may have further contributed to decreased malaria prevalence (11). This study also found that when participants were ill, most preferred to seek treatment from the healthcare facilities in the public sector. Over the past decade, health-seeking behaviour in Meghalaya has evolved significantly. Traditionally, communities relied on tribal medicines for personal health concerns (12). However, with increasing government healthcare initiatives and growing public health awareness, there has been a shift toward utilising modern healthcare system facilities. Programs under the National Health Mission (NHM), such as the Tribal Health Initiative, have played a significant role in improving access to healthcare services (13). These changes reflect broader trends in health-seeking behaviour among India's tribal populations, where access to healthcare and growing awareness have driven this shift (13). This suggests that the study likely captures an accurate estimate of malaria’s true point prevalence, as individuals actively presenting at health facilities allow for the detection of a broader spectrum of disease cases, ranging from mild to severe. More than half of infected individuals had sub-microscopic infections, detectable only by RDT and PCR-based methods. These results are similar to the earlier community-based, active surveillance in KH and JH (4). As sub-microscopic carriers contribute to Plasmodium transmission (14), regular use of more sensitive and specific diagnostic tests, such as PCR, will improve diagnostic accuracy in low-prevalence settings (14), thereby enhancing case detection and further supporting the malaria elimination efforts. Plasmodium falciparum has been documented as the most common species in Meghalaya (2,4). In this study too, it represented 60% of all infections, with P. vivax present in 38% of detected cases Here, P. vivax infections were observed in one health centre in JH. Differences in patterns of Plasmodium species across regions may be important as understanding species distributions helps in identifying high-risk regions where tailored control measures may be implemented, such as antimalarial treatments for chronic P. vivax infection (15). A history of malaria within the past 12 months was associated with increased risk of current Plasmodium infection, consistent with findings from a previous community-based study conducted in Meghalaya (4). Recurrent episodes of malaria have previously been reported in a small proportion of individuals from endemic regions (16,17). Malaria recurrence can occur for several reasons, such as the return of parasites (recrudescence), dormant liver stages (relapses), or new infections (16). Taken together, it highlights the need for ongoing monitoring and targeted interventions like Reactive Case Detection (RCD) and foci investigation for those with recent malaria case history (18,19), along with improved access to treatment and strengthened preventive measures to reduce disease burden. In this study, people engaging in outdoor activities during the evening and early morning hours had a higher risk of Plasmodium infection. This finding aligns with another study in Odisha, India that showed a correlation between outdoor exposure during these times and heightened malaria risk (20). Traditionally, primary Anopheles vector species are considered to bite late at night (21), which meant evening activities were not expected to pose significant exposure risk. However, recent research indicates that some Anopheles species are changing their host-seeking behaviour – biting earlier in the evening, later in the morning, and outdoors (22). This shift increases Plasmodium transmission risk during evening or morning activities such as fetching water, preparing food, or socialising (23,24). These periods are particularly concerning because many individuals remain unprotected by ITNs or indoor spraying when competent vectors are active (22,25). Collectively, these findings suggest that while the use of protective measures such as ITNs is effective indoors, individuals who are active outdoors during the evening and early morning remain at risk, underscoring the need for targeted interventions such as the implementation of larval source management (26) and risk communication to address this gap in malaria control. Almost all study participants reported using ITNs, consistent with findings from previous community-based studies in Meghalaya which also highlighted the widespread use of LLINs throughout the region (9) and that they were preferred given their perceived effectiveness and durability (27). The current finding is noteworthy, as widespread use of LLINs is a cornerstone of India’s malaria prevention efforts (28). LLINs not only serve as an effective physical barrier against mosquito bites but also help to reduce Plasmodium transmission (29), contributing to the broader goal of public health programs focused on controlling and ultimately eliminating malaria. The findings from this study have implications for both clinicians and public health policymakers. Clinicians must remain vigilant and proactive in malaria-endemic areas to ensure timely diagnosis and appropriate treatment, particularly in low-endemic areas where prevalence is lower but transmission still occurs (30). For policymakers, these insights highlight the need for region-specific malaria control strategies, targeted resource allocation, and enhanced surveillance efforts to detect persistent low-level transmission, prevent outbreaks, and maintain progress in malaria elimination. This study has several limitations. As a facility-based study, it may have missed patients who sought care at other facilities or those who self-medicated. Additionally, the true prevalence of P. vivax malaria may have been underestimated as asymptomatic infections with low parasite densities, who are less likely to seek treatment (31), would have gone undetected. Since participants were enrolled from public health facilities, the findings may not fully represent the health-seeking behaviours of all individuals residing in the study area, although participants of qualitative study that interviewed members from the same communities reported similar health-seeking behaviour (27). Overall, continued surveillance, targeted interventions, and improved access to prevention and treatment are crucial for reducing malaria in the region. These findings highlight the importance of accounting for local factors, particularly community-specific behaviours, in the design of effective malaria control measures. Outdoor activities, especially during the evening and early morning when mosquitoes are most active, contribute significantly to malaria risk. By taking these local behaviours into account, targeted prevention strategies such as outdoor mosquito control and improved community education can be developed to protect more effectively those at greatest risk. Declarations Ethics approval and consent to participate Approval to undertake the study was obtained from the Institutional Review Board at New York University, New York, NY, USA and the University Research Ethics Committee of Martin Luther Christian University, Shillong, Meghalaya, India. Written informed consent was obtained from all adult participants (≥ 18 years of age). Assent was obtained for participants aged 7–17 years, in addition to the parental consent. Consent for publication Not applicable. Availability of data and materials Data generated in this study are available through the open-access online resource for population-based epidemiological studies ClinEpiDB (https://clinepidb.org) at https://clinepidb.org/ce/app/record/dataset/DS_4670e06911. Competing interests The authors declare that they have no competing interests. Funding Research reported in this publication was supported by the US National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number U19AI089676. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. . This manuscript is the result of funding in whole or in part by the National Institutes of Health (NIH). It is subject to the NIH Public Access Policy. Through acceptance of this federal funding, NIH has been given a right to make this manuscript publicly available in PubMed Central upon the Official Date of Publication, as defined by NIH. Authors' information Authors and Affiliations MLC University, National Lutheran Health and Medical Board (NLHMB), Shillong, India Phibansuk Lyngdoh, Rajiv Sarkar, Innang Lyngdoh & Sandra Albert Indian Institute of Public Health Shillong, Meghalaya, India Phibansuk Lyngdoh, Rajiv Sarkar, Innang Lyngdoh & Sandra Albert University of Michigan School of Public Health, Ann Arbor, Michigan, United States Mark L. Wilson New York University, New York, New York, United States Anne Kessler & Jane M. Carlton Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States Anne Kessler & Jane M. Carlton Author’s contributions AK, JC and SA conceived and designed study and undertook the data collection; PL, RS and MLW cleaned the data and performed the data analyses; IL completed the DNA extractions and PCR amplifications for the study; PL, RS and MLW wrote the manuscript with input from all authors. All authors read and approved the final manuscript. Acknowledgements We are deeply grateful to the study participants for their willingness and involvement. Our sincere thanks go to the Department of Health and Family Welfare, Government of Meghalaya, and the Meghalaya State Programme Management Unit, National Vector-Borne Disease Control Programme, for granting permission to carry out this study and for their continuous support and collaborative efforts. We acknowledge the support of Anna Maria van Eijk for her help with the study design and Steven A. Sullivan for data management. We would also like to extend our appreciation to the IIPH-Shillong staff, especially Christine Manar, Manroi Challam, Enrichson Suting, Watson Siangshai, Jurysha Nongdhar, Charisma Khongwir, and Peter Marbaniang, for their diligent work in data collection and sample processing. A special thanks to Bandapkupar Mawkhlieng and Innang Sangniang for their valuable contributions in the laboratory analysis. References Kessler A, Shylla B, Singh US, Lyngdoh R, Mawkhlieng B, Van Eijk AM, et al. Spatial and temporal village-level prevalence of Plasmodium infection and associated risk factors in two districts of Meghalaya, India. Malar J. 2021 Feb 4;20(1):70. Kessler A, Van Eijk AM, Jamir L, Walton C, Carlton JM, Albert S. Malaria in Meghalaya: a systematic literature review and analysis of data from the National Vector-Borne Disease Control Programme. Malar J. 2018 Dec;17(1):411. Dev V, Sangma BM, Dash AP. 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Human Exposure to Early Morning Anopheles funestus Biting Behavior and Personal Protection Provided by Long-Lasting Insecticidal Nets. Vontas J, editor. PLoS ONE. 2014 Aug 12;9(8):e104967. García GA, Fuseini G, Donfack OT, Wofford RN, Nlang JAM, Efiri PB, et al. The need for larval source management accompanying urban development projects in malaria endemic areas: a case study on Bioko Island. Malar J. 2022 Nov 14;21(1):328. Nengnong CB, Passah M, Wilson ML, Bellotti E, Kessler A, Marak BR, et al. Community and health worker perspectives on malaria in Meghalaya, India: Covering the last mile of elimination by 2030 [Internet]. 2023 [cited 2025 Jan 7]. Available from: https://www.researchsquare.com/article/rs-3431734/v1 National Strategic Plan: Malaria Elimination 2023-27, National Centre for Vector Borne Disease Control, Govt. of India [Internet]. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://ncvbdc.mohfw.gov.in/Doc/National-Strategic-Plan-Malaria-2023-27.pdf Pryce J, Richardson M, Lengeler C. Insecticide-treated nets for preventing malaria. Cochrane Infectious Diseases Group, editor. Cochrane Database Syst Rev [Internet]. 2018 Nov 6 [cited 2025 Jan 13]; Available from: https://doi.wiley.com/10.1002/14651858.CD000363.pub3 White NJ, Pukrittayakamee S, Hien TT, Faiz MA, Mokuolu OA, Dondorp AM. Malaria. The Lancet. 2014 Feb;383(9918):723–35. Howes RE, Battle KE, Mendis KN, Smith DL, Cibulskis RE, Baird JK, et al. Global Epidemiology of Plasmodium vivax . Am J Trop Med Hyg. 2016 Dec 28;95(6 Suppl):15–34. Tables Table 1 and 2 are available in the Supplementary Files section. Table 3: Risk factors for testing positive for Plasmodium spp. infection overall, and by study area Characteristic or Behavior All Sites (n=1031) South Garo Hills (n=114) West Jaintia Hills (n= 722) West Khasi Hills (n=195) OR (95% CI) p- value OR (95% CI) p- value OR (95% CI) p- value OR (95% CI) p- value Age below 18 years 1.7 (0.9-3.2) 0.066 0.8 (0.3-2.0) 0.732 3.5 (1.3-9.5) 0.010 2.3 (0.1-38.9) 0.547 Male gender 0.9 (0.5-1.6) 0.620 0.5 (0.1-1.2) 0.147 1.6 (0.6-4.2) 0.260 0.8 (0.04-13.2) 0.880 No formal education 0.5 (0.2-1.0) 0.038 0.4 (0.1-3.3) 0.412 0.8 (0.3-2.2) 0.806 - - Occupation: Agricultural related/ Daily wage/labor 0.5 (0.3-1.1) 0.078 2.6 (0.7-9.0) 0.118 0.6 (0.2-1.7) 0.394 0.6(0.03-10.6) 0.760 Travelled for 14 days or more 1.2 (0.5-3.3) 0.617 2.5 (0.4-13.1) 0.280 1.6 (0.4-5.6) 0.453 # # Stay a night in the field 2.0 (0.9-4.8) 0.080 19.0 (1.7-203.2) 0.015 1.9 (0.6-5.7) 0.199 # # Malaria reported in past 12 months 9.2 (4.9-17.7) <0.001 6.7 (2.6-16.9) <0.001 2.3 (0.2-18.9) 0.412 # # Activity outside house before bedtime 2.0 (1.1-3.7) 0.023 4.8 (1.3-18.1) 0.018 # # # # Wake up time before 6am 0.4 (0.1-1.8) 0.243 2.1 (0.8-5.8) 0.112 0.4 (0.1-1.9) 0.288 # # Before 6am activity outside house 3.1 (1.3-7.4) 0.010 3.3 (0.3-31.7) 0.295 2.6 (0.5-12.1) 0.213 # # Do not use bed net at night 1.6 (0.5-5.8) 0.396 1.4 (0.1-12.9) 0.743 3.0 (0.6-13.9) 0.148 # # Use bed net sometimes 0.3 (0.1-1.3) 0.121 0.4 (0.1-2.2) 0.354 0.3 (0.04-2.3) 0.256 # # Cover arms and legs 1.4 (0.7-2.7) 0.372 # # 0.4 (0.1-1.2) 0.129 # # Use coil 0.4 (0.2-0.7) 0.004 # # 0.3 (0.1-0.8) 0.021 # # Use mats 0.5 (0.1-4.5) 0.618 # # 1.1 (0.1-9.0) 0.884 # # Use insecticide cream 1.1 (0.5-2.6) 0.738 1.1 (0.4-2.9) 0.862 0.3 (0.01-2.9) 0.360 # # Household not sprayed 1.1 (0.6-2.1) 0.729 1.7 (0.6-4.4) 0.231 0.7 (0.2-1.8) 0.527 # # # Odds ratio (95% CI) and p-value could not be estimated because of separation due to small number of participants with Plasmodium infection. Additional Declarations No competing interests reported. Supplementary Files Table1and2.docx Cite Share Download PDF Status: Published Journal Publication published 12 Dec, 2025 Read the published version in Malaria Journal → Version 1 posted Editorial decision: Revision requested 11 Sep, 2025 Reviews received at journal 02 Sep, 2025 Reviews received at journal 01 Sep, 2025 Reviewers agreed at journal 22 Jul, 2025 Reviewers agreed at journal 21 Jul, 2025 Reviewers invited by journal 21 Jul, 2025 Editor assigned by journal 17 Jul, 2025 Submission checks completed at journal 17 Jul, 2025 First submitted to journal 16 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7138239","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489085598,"identity":"fe63f8f6-b080-4936-bf06-c9e1c41c4fd9","order_by":0,"name":"Phibansuk Lyngdoh","email":"","orcid":"","institution":"MLC University, National Lutheran Health and Medical Board (NLHMB)","correspondingAuthor":false,"prefix":"","firstName":"Phibansuk","middleName":"","lastName":"Lyngdoh","suffix":""},{"id":489085599,"identity":"f8a6e657-5527-40ef-880b-09814ab8ffe1","order_by":1,"name":"Rajiv Sarkar","email":"","orcid":"","institution":"MLC University, National Lutheran Health and Medical Board (NLHMB)","correspondingAuthor":false,"prefix":"","firstName":"Rajiv","middleName":"","lastName":"Sarkar","suffix":""},{"id":489085600,"identity":"7975bbdf-d85f-4cf6-b905-acb602dcebff","order_by":2,"name":"Mark L. Wilson","email":"","orcid":"","institution":"University of Michigan School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"L.","lastName":"Wilson","suffix":""},{"id":489085601,"identity":"2023ef54-861d-447b-9cd2-709f6aa428f2","order_by":3,"name":"Innang Lyngdoh","email":"","orcid":"","institution":"MLC University, National Lutheran Health and Medical Board (NLHMB)","correspondingAuthor":false,"prefix":"","firstName":"Innang","middleName":"","lastName":"Lyngdoh","suffix":""},{"id":489085602,"identity":"38f1d034-aabc-41fa-9f82-e64489401355","order_by":4,"name":"Anne Kessler","email":"","orcid":"","institution":"New York University","correspondingAuthor":false,"prefix":"","firstName":"Anne","middleName":"","lastName":"Kessler","suffix":""},{"id":489085603,"identity":"f81aca95-41ed-45c5-95a3-a0bcf4aacffb","order_by":5,"name":"Jane M. Carlton","email":"","orcid":"","institution":"New York University","correspondingAuthor":false,"prefix":"","firstName":"Jane","middleName":"M.","lastName":"Carlton","suffix":""},{"id":489085604,"identity":"dc5f0d38-17c2-4ce9-a2d4-90cf5d723ff9","order_by":6,"name":"Sandra Albert","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYJACCRDBByYrJHggXAYGHoJa2EDkgTMkaznYBuPiAfLtZw/erqhhkGeTbj72+eM8Cxlz6fYHDD9qGGTMcWgxOJOXbHnmGINhm8yx5BkHt0nwWM45Y8DYc4yBx7IBhxaGHDPJBjYGxjaJHGMGkBaDGzkMDLwNDDwGB3A4rP8NUMs/Bvs2ifzPDAfngLSkP2D8i0cLww2gLY1tDIlAW5gZDjaAtCQYMOOzxeDGG2PLxj6JZKBfjBnOHAP6ZUaOwWEZIAO3w3IMbzZ8s7Htl25+zFBRU2dvLpH+8OGbGht7nA6DAKS4MADiA4RjB8WpJKgdBaNgFIyCkQEAtQBRyGOfb2AAAAAASUVORK5CYII=","orcid":"","institution":"MLC University, National Lutheran Health and Medical Board (NLHMB)","correspondingAuthor":true,"prefix":"","firstName":"Sandra","middleName":"","lastName":"Albert","suffix":""}],"badges":[],"createdAt":"2025-07-16 09:23:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7138239/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7138239/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12936-025-05721-y","type":"published","date":"2025-12-12T15:59:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87664757,"identity":"5851edf8-a021-45fa-83de-d37b391a5c69","added_by":"auto","created_at":"2025-07-27 11:00:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2195391,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Meghalaya, highlighting the health facilities included in the study.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7138239/v1/c98450fc30000360e6e7fb98.png"},{"id":98244736,"identity":"13768aa9-333f-475e-8f94-5c0582aa14ec","added_by":"auto","created_at":"2025-12-15 16:14:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3185636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7138239/v1/a9a2d7d8-366f-42aa-8466-93023807c15c.pdf"},{"id":87664758,"identity":"0b15a6dd-9edc-45e8-8694-4c6aad18d9b2","added_by":"auto","created_at":"2025-07-27 11:00:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26763,"visible":true,"origin":"","legend":"","description":"","filename":"Table1and2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7138239/v1/7d1813b82aa1ead83f2e1a1f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Malaria risk, treatment-seeking, and prevention in Northeastern India: Clinic-based surveillance of persistent transmission","fulltext":[{"header":"Background","content":"\u003cp\u003eHistorically, malaria has been a public health concern in Meghalaya, a state in the northeastern region (NER) of India. Significant progress in controlling transmission has been achieved over the past decade, primarily due to targeted interventions, enhanced disease surveillance, and active community participation in use of preventive measures (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The introduction of artemisinin-based antimalarial drugs for the treatment of malaria and widespread distribution of long-lasting insecticidal nets (LLINs) may have played a role in lowering malaria incidence, although other factors too may have played a role (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). For example, indoor residual spraying (IRS) has served as a complementary control method, though its coverage remains limited in certain areas (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMalaria transmission in Meghalaya occurs year-round, with peak incidence during the monsoon season (May–July) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Travel history is a major risk factor, and individuals with prior malaria episodes also face a higher risk (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Earlier community-based studies from Meghalaya have provided insights into malaria epidemiology, emphasizing the role of behavioural and environmental factors such as vector exposure and human mobility in malaria epidemiology (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite these community-level findings, research on the clinical epidemiology of malaria in Meghalaya remains limited, with little attention given to patient-specific factors influencing malaria prevalence. Understanding these factors is crucial for refining malaria control strategies, identifying high-risk groups, and tracking disease trends. By analysing suspected malaria cases at the health centre level, valuable insights into disease burden and key risk factors can be obtained, helping to strengthen prevention, control, and the more recent move toward elimination (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis facility-based surveillance investigated malaria prevalence among suspected cases presenting at government healthcare facilities in three districts of Meghalaya: West Jaintia Hills (JH), West Khasi Hills (KH), and South Garo Hills (GH). It also assessed the epidemiological patterns, risk factors, and health seeking behaviour of patients with malaria-like symptoms with the goal of helping policymakers and healthcare providers take data-driven decisions to strengthen India’s malaria elimination efforts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy design, area, and period\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMeghalaya is a mountainous, heavily forested state in Northeast India, bordered by the state of Assam in the north and the country of Bangladesh to the south (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The population of Meghalaya is estimated to be over 3.5\u0026nbsp;million, representing predominantly tribal people mostly living in rural, forested settings (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The economy is largely agrarian involving mixed farming. The climate is among the wettest in the world, especially during the rainy season (\u003cem\u003ee.g.\u003c/em\u003e, May-September). With temperatures ranging from 23-28\u003csup\u003eo\u003c/sup\u003eC and high relative humidity (\u0026gt; 70%), the conditions are ideal for mosquito reproduction and perpetual transmission. The area’s major and minor transmission seasons take place between May-July and between September-November, respectively. While both \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e are present across the state, \u003cem\u003eP. falciparum\u003c/em\u003e is predominant in most regions (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA multi-site, facility-based, cross-sectional study was conducted over a three-year period from September 2018 through November 2021 in three districts of Meghalaya. The facilities included: Nonglang Primary Health Centre (PHC) in West Khasi Hills district (KH), Barato PHC and Nartiang PHC in West Jaintia Hills (JH), and Rongara PHC, Siju PHC and Baghmara Civil Hospital in South Garo Hills (GH) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Selection of the six health centres was based on state control programme \u003cem\u003ePlasmodium\u003c/em\u003e infection records with the goal of capturing both high and low prevalence settings in the three districts.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval to undertake the study was obtained from the Institutional Review Board at New York University, New York, NY, USA and the University Research Ethics Committee of Martin Luther Christian University, Shillong, Meghalaya, India. Written informed consent was obtained from all adult participants (\u0026ge;\u0026thinsp;18\u0026thinsp;years of age) and parental consent from participants aged \u0026lt;18 years. Additionally, assent was obtained from participants aged 7\u0026ndash;17 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and sample collection and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSocio-demographic and behavioural information was collected using a standardized questionnaire from individuals aged 1\u0026ndash;69 years who presented to the health centres with malaria-like symptoms, which included\u0026nbsp;fever, chills, sweating, headache, muscle aches, nausea, vomiting, or diarrhoea. Individual questionnaires were administered at the clinic to consenting participants or their parent/guardian (in case of children) in their native language (\u003cem\u003ee.g.,\u0026nbsp;\u003c/em\u003eKhasi, Pnar, Garo), to gather information on age, gender, education, occupation, knowledge of malaria, malaria episodes during previous year, fever episodes during previous 48 hours, travel history (past two weeks), and malaria prevention methods utilised. Questions on malaria-related risk behaviours and practices were also asked.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBlood sample collection and\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003ePlasmodium\u003cem\u003e\u0026nbsp;detection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproximately 1 ml of blood was drawn via finger prick, and \u003cem\u003eP\u003c/em\u003e. \u003cem\u003efalciparum\u003c/em\u003e and/or \u003cem\u003eP. vivax\u003c/em\u003e infections were detected at the point of care using both a bivalent rapid diagnostic test (RDT; FalciVax) and an ultra-sensitive RDT (Abbott Alere). Light microscopy evaluation of Giemsa-stained blood smears and PCR amplification of concentrated DNA extracted from microvette RBC pellets were also performed on all samples. Species-specific \u003cem\u003ePlasmodium\u003c/em\u003e infections were detected using a single-step PCR targeting Pfr364 (for \u003cem\u003eP. falciparum\u003c/em\u003e) and Pvr47 (for \u003cem\u003eP. vivax\u003c/em\u003e) (7). \u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSubject data were collected by electronic data capture and stored in a secure, firewall protected REDCap (Research Electronic Data Capture) database\u0026nbsp;(8). Data analysis was completed in Stata version 17 for Windows (StataCorp, College Station, Texas, USA). Analysis involved a complete-case approach, in which participants with missing data for important variables were eliminated. Summary statistics for continuous variables are presented as mean and standard deviation (SD), and as numbers and percentages (%) for categorical variables. The prevalence of malaria was estimated as the number of \u003cem\u003ePlasmodium\u003c/em\u003e infections divided by the total number of participants from whom a sample was obtained. Associations between socio-demographic, environmental, or behavioural risk factors and \u003cem\u003ePlasmodium\u003c/em\u003e infections were evaluated using logistic regression and reported as odds ratio (OR) with 95% confidence intervals (CI).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePopulation sampled and Individual characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,031 participants were enrolled across six PHCs surveyed in JH (n=722), KH (n=114), and GH (n=195) from September 2018 through November 2021. Blood samples were obtained and tested from all 1,031 participants. The mean (SD) age of participants was 24.1 (15.9) years. Overall, 54.2% of the study participants were female. Of the adult participants (≥18 years), 19.8% had no formal education. About half of all participants (51.3%) were engaged in agricultural-related activities.\u0026nbsp;Malaria in the previous 12 months was reported by 8.2% of participants, while 9% reported a history of travel outside the village in the previous 14 days. About one in ten participants (11.6%) reported spending one or more nights in the field, with a mean (SD) of 5.8 (4.4) nights. Nearly one-quarter (23.5%) were engaged in ‘outdoor activities’ before 6 am. Nearly three-quarters (70.8%) reported using insecticide treated bed nets (ITNs) while staying in the field. Roughly one-third (34.6%) of all participants were familiar with the typical malarial signs and symptoms, which they reported as fever (94.9%), headache (71.9%), chills (78.3%), and body discomfort (54.3%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDistrict level demographics and occupations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe age and gender distributions of participants across the three districts are presented in Table 1, with males comprising between 43.1% and 55.3%. The proportion of adult participants with no formal education ranged from 11.2% to 63.4%. Between 6.9% and 77.5% of the participants were engaged in agricultural-related activities. 5.0% and 34.5% of the participants were housewives.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReported malaria diagnosis and risk behaviours\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn GH, 28.2% of participants (55/195) reported being diagnosed with malaria in the past 12 months, while the proportions were 10.5% (12/114) in KH and 2.4% (17/722) in JH (Table 1). A history of travel in the past 14 days was reported by 10.5% of the participants (76/722) in JH, 7.9% (9/114) in KH, and 4.1% (8/195) in GH. Staying overnight in the field for one or more days were reported by 16.5% (112/679) participants in JH, 4.2% (4/96) in KH, and 5.7% (4/70) in GH. The average (SD) number of days spent overnight in the field was 5.9 (4.5) days in JH, 3.5 (0.7) days in KH, and 4.0 (1.7) days in GH. Outdoor activities before 6 a.m. ‘wake-up’ time were reported by 68.6% (24/35) of participants in GH, 22.7% (55/251) in JH, and 6.8% (5/73) in KH. Knowledge of malaria signs and symptoms was reported by 69.7% (136/195) of participants in GH, 35.1% (40/114) in KH, and 25.1% (181/722) in JH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHealth-seeking behaviour\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNearly all respondents (97.2%) reported that a public healthcare facility (\u003cem\u003ei.e.,\u003c/em\u003e primary health care centre or district hospital) is their first choice for seeking malaria treatment. If ineffective, 25.5% stated they would then seek care at a private clinic. This preference was reported regardless of whether the individual had previously experienced malaria. The proportion of respondents diagnosed with malaria who preferred to seek treatment from government healthcare facilities ranged from 83.3% to 100% across KH, GH, and JH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReported malaria risk reduction\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUse of methods to prevent mosquito bites among participants was also analysed (Table 2). Almost all individuals (96.3%) reported using a bed net at night with virtually all reporting usage regularly (83.9%) or most of the time (11.4%). However, only 75.6% of the bed nets had been treated with insecticide. About half of respondents (55.8%) used clothing that covered their arms and legs to avoid mosquito bites, but 86.1% did not apply insecticide cream to prevent bites. Evening activities were reported by 95.5% of participants, which was usually held within the house. Virtually everyone ate their dinner (99.7%) and slept inside their houses. One quarter (24.5%) of activities recorded in the early morning occurred outside the house.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePlasmodium infection prevalence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlasmodium\u003c/em\u003e infections were found by RDT and/or PCR and/or light microscopy in 4.4% (45/1,031) of individuals. \u003cem\u003ePlasmodium\u003c/em\u003e infection was higher in GH (24/195, 12.3%) than in JH (19/722, 2.6%) and KH (2/114, 1.8%). \u0026nbsp;Of the positives, 10 (22%) were positive by RDT only, 2 (4%) by PCR only, 14 (31%) by both RDT and PCR, 1 (2%) by both RDT and light microscopy, and 18 (40%) by all three methods (\u003cem\u003ee.g.,\u003c/em\u003e RDT, PCR, and light microscopy); no infections were determined solely by microscopy. A slightly higher proportion of PCR-positive infections were reported from GH (18/34 ;40%) than from JH (15/34 ;33.3%) and KH (1/34 ;2%). \u003cem\u003ePlasmodium falciparum\u003c/em\u003e was the only species detected in 60% (27/45) of positive samples, while 38% (17/45) were \u003cem\u003eP. vivax\u003c/em\u003e, and 2% (1/45) were mixed (\u003cem\u003eP. vivax + P. falciparum\u003c/em\u003e). Most of the \u003cem\u003eP. vivax\u003c/em\u003e infections (17/19; 89.4%) were reported from JH. A case of malaria was defined as a positive \u003cem\u003ePlasmodium\u003c/em\u003e infection based on RDT and/or PCR results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRisk factors for\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003ePlasmodium infection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe factors associated with the risk of \u003cem\u003ePlasmodium\u003c/em\u003e infection were assessed collectively and separately for the three districts (Table 3). Statistically significant increased risk was associated with reported history of malaria in the previous 12 months (OR=9.2, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), activity outside the house before bedtime (OR=2.0, \u003cem\u003eP\u003c/em\u003e=0.023), and activity outside the house before 6 am (OR=3.1, \u003cem\u003eP\u003c/em\u003e=0.010). None of the other factors assessed (\u003cem\u003ee.g.,\u0026nbsp;\u003c/em\u003eage, gender, education, occupation, IRS spraying, and LLIN use) were statistically significant.\u003c/p\u003e\n\u003cp\u003eIn GH, the odds of \u003cem\u003ePlasmodium\u003c/em\u003e infection were significantly higher for individuals with a history of malaria in the past 12 months (OR=6.7, \u003cem\u003eP\u003c/em\u003e\u003cstrong\u003e\u0026lt;\u003c/strong\u003e0.001). Staying a night in the field (OR=19.0, \u003cem\u003eP\u003c/em\u003e=0.015) and engaging in activities outside before bedtime (OR=4.8, \u003cem\u003eP\u003c/em\u003e=0.018) were also significantly associated with increased odds of malaria in this district. In JH (OR=3.5, \u003cem\u003eP\u003c/em\u003e=0.010) and (OR=2.3, \u003cem\u003eP\u003c/em\u003e=0.547), younger people (\u0026lt;18 years) had significantly higher odds of \u003cem\u003ePlasmodium\u003c/em\u003e infection this was not statistically significant in KH.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis facility-based surveillance study investigated the prevalence and risk factors of \u003cem\u003ePlasmodium\u003c/em\u003e infection among suspected malaria cases over a three-year period to gain deeper insights into the epidemiology of malaria in three districts of Meghalaya. The overall malaria prevalence among participants who were visiting health centres was 4.4%, consistent with a recent report analysing data from the National Vector Borne Disease Control Program (NVBDCP) (2) and findings from previous active, cross-sectional surveillance conducted in KH and JH (4). \u003cstrong\u003eCollectively\u003c/strong\u003e, these findings indicate a consistent \u003cstrong\u003edecline in malaria\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecases\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein Meghalaya over the past decade\u003c/strong\u003e. This decline can likely be attributed to the shift from sulphadoxine-pyrimethamine treatment to artemether-lumefantrine artemisinin combination therapy in 2013, and the state-wide distribution of LLINs in 2016, 2019 and 2020 (2,9,10). Additionally, advancements in diagnostic and treatment strategies, particularly the involvement of Accredited Social Health Activists (ASHAs) in testing and treating individuals with \u003cem\u003ePlasmodium\u003c/em\u003e infections at the community level, may have further contributed to decreased malaria prevalence (11).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study also found that when participants were ill, most preferred to seek treatment from the healthcare facilities in the public sector. \u0026nbsp;Over the past decade, health-seeking behaviour in Meghalaya has evolved significantly. Traditionally, communities relied on tribal medicines for personal health concerns (12). However, with increasing government healthcare initiatives and growing public health awareness, there has been a shift toward utilising modern healthcare system facilities. Programs under the National Health Mission (NHM), such as the Tribal Health Initiative, have played a significant role in improving access to healthcare services (13). These changes reflect broader trends in health-seeking behaviour among India\u0026apos;s tribal populations, where access to healthcare and growing awareness have driven this shift (13). This suggests that the study likely captures an accurate estimate of malaria\u0026rsquo;s true point prevalence, as individuals actively presenting at health facilities allow for the detection of a broader spectrum of disease cases, ranging from mild to severe.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;More than half of infected individuals had sub-microscopic infections, detectable only by RDT and PCR-based methods. These results are similar to the earlier community-based, active surveillance in KH and JH (4). As sub-microscopic carriers contribute to \u003cem\u003ePlasmodium\u003c/em\u003e transmission (14), regular use of more sensitive and specific diagnostic tests, such as PCR, will improve diagnostic accuracy in low-prevalence settings (14), thereby enhancing case detection and further supporting the malaria elimination efforts.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003ePlasmodium falciparum\u003c/em\u003e has been documented as the most common species in Meghalaya (2,4). In this study too, it represented 60% of all infections, with \u003cem\u003eP. vivax\u003c/em\u003e present in 38% of detected cases Here, \u003cem\u003eP. vivax\u003c/em\u003e infections were observed in one health centre in JH. Differences in patterns of \u003cem\u003ePlasmodium\u003c/em\u003e species across regions may be important as understanding species distributions helps in identifying high-risk regions where tailored control measures may be implemented, such as antimalarial treatments for chronic \u003cem\u003eP. vivax\u003c/em\u003e infection (15).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A history of malaria within the past 12 months was associated with increased risk of current \u003cem\u003ePlasmodium\u003c/em\u003e infection, consistent with findings from a previous community-based study conducted in Meghalaya (4). Recurrent episodes of malaria have previously been reported in a small proportion of individuals from endemic regions (16,17). Malaria recurrence can occur for several reasons, such as the return of parasites (recrudescence), dormant liver stages (relapses), or new infections (16). Taken together, it highlights the need for ongoing monitoring and targeted interventions like Reactive Case Detection (RCD) and foci investigation for those with recent malaria case history (18,19), along with improved access to treatment and strengthened preventive measures to reduce disease burden.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In this study, people engaging in outdoor activities during the evening and early morning hours had a higher risk of \u003cem\u003ePlasmodium\u003c/em\u003e infection. This finding aligns with another study in Odisha, India that showed a correlation between outdoor exposure during these times and heightened malaria risk (20). Traditionally, primary \u003cem\u003eAnopheles\u003c/em\u003e vector species are considered to bite late at night (21), which meant evening activities were not expected to pose significant exposure risk. However, recent research indicates that some \u003cem\u003eAnopheles\u003c/em\u003e species are changing their host-seeking behaviour \u0026ndash; biting earlier in the evening, later in the morning, and outdoors (22). This shift increases \u003cem\u003ePlasmodium\u003c/em\u003e transmission risk during evening or morning activities such as fetching water, preparing food, or socialising (23,24). These periods are particularly concerning because many individuals remain unprotected by ITNs or indoor spraying when competent vectors are active (22,25). Collectively, these findings suggest that while the use of protective measures such as ITNs is effective indoors, individuals who are active outdoors during the evening and early morning remain at risk, underscoring the need for targeted interventions such as the implementation of larval source management (26) and risk communication to address this gap in malaria control.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Almost all study participants reported using ITNs, consistent with findings from previous community-based studies in Meghalaya which also highlighted the widespread use of LLINs throughout the region (9) and that they were preferred given their perceived effectiveness and durability (27). The current finding is noteworthy, as widespread use of LLINs is a cornerstone of India\u0026rsquo;s malaria prevention efforts (28). LLINs not only serve as an effective physical barrier against mosquito bites but also help to reduce \u003cem\u003ePlasmodium\u003c/em\u003e transmission (29), contributing to the broader goal of public health programs focused on controlling and ultimately eliminating malaria.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The findings from this study have implications for both clinicians and public health policymakers. Clinicians must remain vigilant and proactive in malaria-endemic areas to ensure timely diagnosis and appropriate treatment, particularly in low-endemic \u0026nbsp;areas where prevalence is lower but transmission still occurs (30). For policymakers, these insights highlight the need for region-specific malaria control strategies, targeted resource allocation, and enhanced surveillance efforts to detect persistent low-level transmission, prevent outbreaks, and maintain progress in malaria elimination.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study has several limitations. As a facility-based study, it may have missed patients who sought care at other facilities or those who self-medicated. Additionally, the true prevalence of \u003cem\u003eP. vivax\u003c/em\u003e malaria may have been underestimated as asymptomatic infections with low parasite densities, who are less likely to seek treatment (31), would have gone undetected. Since participants were enrolled from public health facilities, the findings may not fully represent the health-seeking behaviours of all individuals residing in the study area, although participants of qualitative study that interviewed members from the same communities reported similar health-seeking behaviour (27).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOverall, continued surveillance, targeted interventions, and improved access to prevention and treatment are crucial for reducing malaria in the region. These findings highlight the importance of accounting for local factors, particularly community-specific behaviours, in the design of effective malaria control measures. Outdoor activities, especially during the evening and early morning when mosquitoes are most active, contribute significantly to malaria risk. By taking these local behaviours into account, targeted prevention strategies such as outdoor mosquito control and improved community education can be developed to protect more effectively those at greatest risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval to undertake the study was obtained from the Institutional Review Board at New York University, New York, NY, USA and the University Research Ethics Committee of Martin Luther Christian University, Shillong, Meghalaya, India. Written informed consent was obtained from all adult participants (≥ 18 years of age). Assent was obtained for participants aged 7–17 years, in addition to the parental consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData generated in this study are available through the open-access online resource for population-based epidemiological studies ClinEpiDB (https://clinepidb.org) at https://clinepidb.org/ce/app/record/dataset/DS_4670e06911.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch reported in this publication was supported by the US National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number U19AI089676. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. . This manuscript is the result of funding in whole or in part by the National Institutes of Health (NIH). It is subject to the NIH Public Access Policy. Through acceptance of this federal funding, NIH has been given a right to make this manuscript publicly available in PubMed Central upon the Official Date of Publication, as defined by NIH. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors and Affiliations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMLC University, National Lutheran Health and Medical Board (NLHMB), Shillong, India\u003c/p\u003e\n\u003cp\u003ePhibansuk Lyngdoh, Rajiv Sarkar, Innang Lyngdoh \u0026amp; Sandra Albert\u003c/p\u003e\n\u003cp\u003eIndian Institute of Public Health Shillong, Meghalaya, India\u003c/p\u003e\n\u003cp\u003ePhibansuk Lyngdoh, Rajiv Sarkar, Innang Lyngdoh \u0026amp; Sandra Albert\u003c/p\u003e\n\u003cp\u003eUniversity of Michigan School of Public Health, Ann Arbor, Michigan, United States\u003c/p\u003e\n\u003cp\u003eMark L. Wilson\u003c/p\u003e\n\u003cp\u003eNew York University, New York, New York, United States\u003c/p\u003e\n\u003cp\u003eAnne Kessler \u0026amp; Jane M. Carlton\u003c/p\u003e\n\u003cp\u003eJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States\u003c/p\u003e\n\u003cp\u003eAnne Kessler \u0026amp; Jane M. Carlton\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor’s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAK, JC and SA conceived and designed study and undertook the data collection; PL, RS and MLW cleaned the data and performed the data analyses; IL completed the DNA extractions and PCR amplifications for the study; PL, RS and MLW wrote the manuscript with input from all authors. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are deeply grateful to the study participants for their willingness and involvement. Our sincere thanks go to the Department of Health and Family Welfare, Government of Meghalaya, and the Meghalaya State Programme Management Unit, National Vector-Borne Disease Control Programme, for granting permission to carry out this study and for their continuous support and collaborative efforts. We acknowledge the support of Anna Maria van Eijk for her help with the study design and Steven A. Sullivan for data management. We would also like to extend our appreciation to the IIPH-Shillong staff, especially Christine Manar, Manroi Challam, Enrichson Suting, Watson Siangshai, Jurysha Nongdhar, Charisma Khongwir, and Peter Marbaniang, for their diligent work in data collection and sample processing. A special thanks to Bandapkupar Mawkhlieng and Innang Sangniang for their valuable contributions in the laboratory analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKessler A, Shylla B, Singh US, Lyngdoh R, Mawkhlieng B, Van Eijk AM, et al. 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Outdoor-sleeping and other night-time activities in northern Ghana: implications for residual transmission and malaria prevention. Malar J. 2015 Dec;14(1):35. \u003c/li\u003e\n\u003cli\u003eMonroe A, Moore S, Koenker H, Lynch M, Ricotta E. Measuring and characterizing night time human behaviour as it relates to residual malaria transmission in sub-Saharan Africa: a review of the published literature. Malar J. 2019 Dec;18(1):6. \u003c/li\u003e\n\u003cli\u003eMoiroux N, Damien GB, Egrot M, Djenontin A, Chandre F, Corbel V, et al. Human Exposure to Early Morning Anopheles funestus Biting Behavior and Personal Protection Provided by Long-Lasting Insecticidal Nets. Vontas J, editor. PLoS ONE. 2014 Aug 12;9(8):e104967. \u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a GA, Fuseini G, Donfack OT, Wofford RN, Nlang JAM, Efiri PB, et al. The need for larval source management accompanying urban development projects in malaria endemic areas: a case study on Bioko Island. Malar J. 2022 Nov 14;21(1):328. \u003c/li\u003e\n\u003cli\u003eNengnong CB, Passah M, Wilson ML, Bellotti E, Kessler A, Marak BR, et al. Community and health worker perspectives on malaria in Meghalaya, India: Covering the last mile of elimination by 2030 [Internet]. 2023 [cited 2025 Jan 7]. Available from: https://www.researchsquare.com/article/rs-3431734/v1\u003c/li\u003e\n\u003cli\u003eNational Strategic Plan: Malaria Elimination 2023-27, National Centre for Vector Borne Disease Control, Govt. of India [Internet]. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://ncvbdc.mohfw.gov.in/Doc/National-Strategic-Plan-Malaria-2023-27.pdf\u003c/li\u003e\n\u003cli\u003ePryce J, Richardson M, Lengeler C. Insecticide-treated nets for preventing malaria. Cochrane Infectious Diseases Group, editor. Cochrane Database Syst Rev [Internet]. 2018 Nov 6 [cited 2025 Jan 13]; Available from: https://doi.wiley.com/10.1002/14651858.CD000363.pub3\u003c/li\u003e\n\u003cli\u003eWhite NJ, Pukrittayakamee S, Hien TT, Faiz MA, Mokuolu OA, Dondorp AM. Malaria. The Lancet. 2014 Feb;383(9918):723\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003eHowes RE, Battle KE, Mendis KN, Smith DL, Cibulskis RE, Baird JK, et al. Global Epidemiology of \u003cem\u003ePlasmodium vivax\u003c/em\u003e. Am J Trop Med Hyg. 2016 Dec 28;95(6 Suppl):15\u0026ndash;34. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eRisk factors for testing positive for \u003cem\u003ePlasmodium\u003c/em\u003e spp. infection overall, and by study area\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"775\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eCharacteristic or Behavior\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eAll Sites\u003c/p\u003e\n \u003cp\u003e(n=1031)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eSouth Garo Hills\u003c/p\u003e\n \u003cp\u003e(n=114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eWest Jaintia Hills\u003c/p\u003e\n \u003cp\u003e(n= 722)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eWest Khasi Hills\u003c/p\u003e\n \u003cp\u003e(n=195)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep- value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep- value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep- value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep- value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eAge below 18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.7 (0.9-3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.8 (0.3-2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e3.5 (1.3-9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2.3 (0.1-38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eMale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.9 (0.5-1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.5 (0.1-1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.6 (0.6-4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.8 (0.04-13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.5 (0.2-1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.4 (0.1-3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.8 (0.3-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eOccupation: Agricultural related/ Daily wage/labor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.5 (0.3-1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e2.6 (0.7-9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.6 (0.2-1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e0.6(0.03-10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eTravelled for 14 days or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.2 (0.5-3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e2.5 (0.4-13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.6 (0.4-5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eStay a night in the field\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.0 (0.9-4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e19.0 (1.7-203.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.9 (0.6-5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eMalaria reported in past 12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9.2 (4.9-17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e6.7 (2.6-16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e2.3 (0.2-18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eActivity outside house before bedtime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.0 (1.1-3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e4.8 (1.3-18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eWake up time before 6am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.4 (0.1-1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e2.1 (0.8-5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.4 (0.1-1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eBefore 6am activity outside house\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e3.1 (1.3-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e3.3 (0.3-31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e2.6 (0.5-12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eDo not use bed net at night\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.6 (0.5-5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.4 (0.1-12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e3.0 (0.6-13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eUse bed net sometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.3 (0.1-1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.4 (0.1-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.3 (0.04-2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eCover arms and legs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.4 (0.7-2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.4 (0.1-1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eUse coil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.4 (0.2-0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.3 (0.1-0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eUse mats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.5 (0.1-4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.1 (0.1-9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eUse insecticide cream\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.1 (0.5-2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.1 (0.4-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.3 (0.01-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eHousehold not sprayed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.1 (0.6-2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.7 (0.6-4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.7 (0.2-1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e# Odds ratio (95% CI) and p-value could not be estimated because of separation due to small number of participants with \u003cem\u003ePlasmodium\u003c/em\u003e infection.\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Northeast India, Malaria, Prevalence, Risk factors, Plasmodium infection","lastPublishedDoi":"10.21203/rs.3.rs-7138239/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7138239/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eMalaria has historically been a public health concern in Meghalaya with year-round transmission peaking during the monsoon and post-monsoon seasons. This study investigated malaria prevalence among suspected cases presenting at health centres across three districts of Meghalaya, in the northeastern region (NER) of India.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA multi-site, facility-based, cross-sectional study was conducted in five primary health centres (PHC) and one district hospital from three geographically distinct regions of Meghalaya: West Khasi Hills [KH] district, West Jaintia Hills [JH] district, and South Garo Hills [GH] district. Individuals presenting at the selected healthcare facilities with malaria-like symptoms between 2018 and 2021 were enrolled. Malaria cases were detected by light microscopy, RDT, and PCR. Malaria prevalence was estimated as the number of \u003cem\u003ePlasmodium\u003c/em\u003e infections divided by the total number of participants providing a blood sample. Logistic regression analysis was conducted to assess the risk factors of malaria.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 1,031 participants provided a blood sample for testing. Forty-five (4.4%) participants had a \u003cem\u003ePlasmodium\u003c/em\u003e infection, most (60%) of which were \u003cem\u003eP. falciparum\u003c/em\u003e. Malaria prevalence ranged from 1.8% in KH to 12.3% in GH. Diagnosis of malaria within the past 12 months (OR\u0026thinsp;=\u0026thinsp;9.2; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and performing outdoor activities before bedtime (OR\u0026thinsp;=\u0026thinsp;2.0; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023) or early morning (OR\u0026thinsp;=\u0026thinsp;3.1; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) were significantly associated with \u003cem\u003ePlasmodium\u003c/em\u003e infection.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe results provide valuable insights into the epidemiology of malaria in an endemic region in NER of India. These findings emphasize the importance of considering specific local risk-factors, such as behavioural patterns, in designing effective malaria control strategies.\u003c/p\u003e","manuscriptTitle":"Malaria risk, treatment-seeking, and prevention in Northeastern India: Clinic-based surveillance of persistent transmission","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-27 11:00:15","doi":"10.21203/rs.3.rs-7138239/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-11T17:00:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T03:54:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T14:59:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21401526374181497340793112792964966665","date":"2025-07-22T09:45:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284709543770911264570144629657720760957","date":"2025-07-21T13:02:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-21T12:32:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-17T14:14:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-17T14:13:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2025-07-16T09:17:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d574a757-226e-4573-8200-85a89c7cda22","owner":[],"postedDate":"July 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:09:00+00:00","versionOfRecord":{"articleIdentity":"rs-7138239","link":"https://doi.org/10.1186/s12936-025-05721-y","journal":{"identity":"malaria-journal","isVorOnly":false,"title":"Malaria Journal"},"publishedOn":"2025-12-12 15:59:03","publishedOnDateReadable":"December 12th, 2025"},"versionCreatedAt":"2025-07-27 11:00:15","video":"","vorDoi":"10.1186/s12936-025-05721-y","vorDoiUrl":"https://doi.org/10.1186/s12936-025-05721-y","workflowStages":[]},"version":"v1","identity":"rs-7138239","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7138239","identity":"rs-7138239","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}