Malaria risk factors amongst forest going populations in Mondulkiri Province and Kampong Speu Province, Cambodia: a large cross-sectional survey

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This study explores malaria risk factors amongst forest-exposed groups in Mondulkiri and Kampong Speu Provinces, Cambodia as part of a multi-stage study on novel bite prevention tools (Project BITE). Methods: A serial cross-sectional survey explored the demographics, housing structure openness, mosquito bite prevention habits, and gaps in protection amongst three target groups: forest goers who work in the forest, forest dwellers who live in the forest, and forest rangers who patrol forested regions. Malaria prevalence data was collected at three time points using rapid diagnostic tests (RDTs) for febrile individuals and qPCR for all participants. Infection locations and travel patterns of P. falciparum-infected individuals were analyzed for clustering and the potential movement of infections. Results: 2,935 participants were enrolled between October 2022 and February 2023, consisting of 1,093 (37%) forest goers and 1,787 (61%) forest dwellers across both provinces, and 55 (5%) forest rangers in Mondulkiri province. Most worked outdoors as farmers, day laborers, and forest collectors, and reported going to the forest five to seven days a week. For housing, 29% and 39% of participants reported living in partially open primary and secondary structures, respectively. The main methods of mosquito bite protection used were insecticide-treated nets, wearing long sleeves, and burning mosquito coils, with gaps in protection during the daytime and outside at night. All febrile individuals had negative RDT test results. For qPCR, 24 P. falciparum infections (<1%) were detected among forest goers and dwellers, clustered in Pu Trom and Pu Nhav villages in Mondulkiri Province, and Banteay Roka and Banteay Roka Kirisenchey (M) villages in Kampong Speu Province. P. vivax cases were detected (216 cases, 5%) across all enrolled villages. Only two infections were found in forest rangers. Conclusion: Malaria elimination strategies for forest-exposed populations in Cambodia should focus on vector intervention strategies that offer protection during the day and outside at night, and the use of drug-based strategies to clear subpatent infections, targeting forest goers and dwellers in villages where cases are detected. malaria malaria elimination vulnerable population forest malaria forest dweller vector control mosquito volatile pyrethroid spatial repellent insecticide-treated clothing Figures Figure 1 Figure 2 Figure 3 Background The Greater Mekong Subregion has made tremendous progress towards its goal to eliminate human malaria by 2030 [ 1 ]. This region has the highest prevalence of Plasmodium falciparum parasites that are resistant to artemisinin-class antimalarial drugs, and intensive efforts to eliminate this species of malaria regionally have contributed to a 97% reduction in malaria deaths, and 77% reduction in all malaria cases between 2012 and 2022 [ 2 ]. Within this region, Cambodia, the epicenter of drug-resistant P. falciparum parasites, is undergoing last mile efforts for elimination, with only 1,384 infections detected in 2023 [ 3 ] and no malaria-related deaths reported in country since 2017. Remaining infections are concentrated in remote locations in forested areas, often along international borders [ 4 ]. To meet its goals to eliminate human malaria nationally by 2025 [ 5 , 6 ], Cambodia will need to clear malaria infections among high-risk populations in highly forested locations where access to healthcare is poor [ 7 – 9 ] and outdoor malaria transmission is common [ 10 – 13 ]. This project is a part of a multi-stage study, Project Bite Interruption Towards Elimination (BITE), on novel mosquito bite prevention tools in a “forest pack” intended to guide the last mile efforts in Cambodia and potentially other locations challenged by outdoor malaria transmission. In earlier phases of the study a pilot study was conducted in Mondulkiri province investigating malaria risk factors [ 14 ], the efficacy of insecticide treated clothing and spatial repellents to prevent mosquito bites [ 15 , 16 ], and their acceptability among users [ 14 ]. Results were applied to this project, which is a large-scale risk factor assessment to characterize high-risk populations in Mondulkiri and Kampong Speu provinces. Villages included in this study are some of the highest incidence malaria settings remaining in Cambodia [ 12 ], where malaria elimination efforts have been challenged by a high prevalence of outdoor-biting vectors including An. dirus, An. minimus , and An. maculatus mosquitoes [ 7 , 8 , 11 , 12 , 17 ]. In addition to risk factor investigation this study includes malaria diagnosis data using rapid diagnostic tests (RDTs) and qPCR, providing insight on the nature of infections (symptomatic versus asymptomatic), whether they are geographically clustered, and whether human movement is a factor affecting transmission patterns. Additional outcomes from the parent study, including the rollout and user acceptability of mosquito bite prevention tools to this cohort, will be reported elsewhere. Methods Study design This was a serial cross-sectional survey among forest-exposed individuals. Data was collected at three timepoints: October 2022 (Timepoint 0; T0) for baseline data collection, and two follow-up timepoints in December 2022 (T1), and February 2023 (T2). Due to loss to follow-up, additional participants were recruited in T1. Most risk factors were identified from the baseline survey for new participants recruited at T0, such as their demographics, housing structures, previous history of malaria infection, and malaria prevention tools in use prior to study initiation. New participants recruited in T1 had basic demographic data collected, and for some variables we used results collected in T1 and T2, for example time spent in the forest, to gain further insight on whether those risk factors changed throughout the malaria season. At all three timepoints, malaria diagnosis was also conducted using RDTs for febrile individuals and dried blood spots collected for all individuals for subsequent identification of parasite infection using qPCR [ 18 ]. All positive cases identified were mapped to villages where participants resided, to check for clustering patterns. For P. falciparum , travel patterns were investigated for potential associations between human movement and parasite incidence. This was not done for P. vivax because incident infections could either be new ones or relapses. Study location and population This study took place in Mondulkiri Province and Kampong Speu Province, Cambodia (Fig. 1 ), where malaria peak case rates occur during the rainy season from August to January. The targeted study population included three high-risk populations for malaria: forest goers, forest dwellers, and forest rangers [ 10 , 13 – 17 ], the first two of which were defined during the pilot phase of this study [ 14 ]. Forest goers were individuals who lived at least 1 kilometer from the forest, traveling to the forest regularly for seasonal farming, hunting, or foraging (mushrooms, vegetables, and resin) or seasonal migration for gem mining, logging, and plantation work [ 11 , 14 ]. Forest dwellers survived on subsistence farming, living in the forest or within 1 kilometer of its fringes in a traditional house in a village for at least part of the year. Many forest dwellers also had a more open, temporary structure in the farm or forest that they migrated to during planting and harvesting seasons referred to as secondary living structures [ 14 ]. Forest rangers were recruited from Mondulkiri province only; they worked for government or wildlife and conservation agencies that protect the forest and areas near international borders, staying in ranger stations or outdoor hammocks up to 16 nights per month when they were on patrol [ 14 ]. Villages for the study were selected based on consultation with the Cambodian National Center for Parasitology, Entomology and Malaria Control (CNM), who identified locations with actively identified P. falciparum foci that would likely benefit from receiving vector control forest packs for the parent study. “Village” refers to geographic regions that contain residential living structures or ranger stations in forested or non-forested locations, which were defined based on an administrative level within the Cambodian governmental system. Inclusion Criteria Individuals eligible for inclusion had to: Reside in a village selected for the parent study, which required that they: Were accessible by automobile or motorbike from September through January Had access to routine malaria data Had leaders with existing relationships with both the government and implementing partner Meet the definition of one of the three target populations at the time of enrollment: Forest goer: lived outside the forest (more than 1 km from forest edge) with self-reported travel into the forest at least 15% of the time (approximately 1 day a week) Forest dweller: lived in a village in the forest (or within 1 km of forest edge) Forest ranger: actively conducted forest patrol activities and was based at a ranger station Be willing to meet study staff on a monthly basis for study follow-up activities, including meetings and the collection of finger prick blood samples for malaria testing. Be age ≥ 3 years Provide informed consent if aged ≥ 18 years, or obtain consent from guardian if participant is < 18 years of age Speak Khmer and/or Bunong language Recruitment Individuals from the three target populations were recruited using different methods. For forest goers and dwellers, the study team worked closely with the local government, implementing partners, village chiefs, and other influential members of the communities, to gain support for the study and determine the best methods for participant recruitment. To recruit forest rangers, our study team partnered with the Wildlife Conservation Society (WCS), engaging with manager-level forest rangers in three ranger stations in Mondulkiri province only, because there were very few ranger stations operating in Kampong Speu. When recruiting prospective participants, the study team introduced themselves and checked if individuals met the study inclusion criteria. Those eligible and interested to partake in the study were provided with detailed information about the study including the purpose of the project, potential risks and benefits of participation, project duration, and expectations of participants for the study. The study team emphasized that individuals could refuse enrolment in the study or remove themselves from the study at any time without repercussion. After these details were provided, informed consent was sought in Khmer or Bunong. Those able to read were given the informed consent form, and those unable to read had the form read aloud to them. Those who provided informed consent were then enrolled in the study. Eligible individuals from each village were recruited until the target number of participants was reached. Data collection and analysis At T0, a survey questionnaire was administered to all participants capturing village, household, and individual-level demographic information, housing construction, and use of vector control tools at baseline. At T1 and T2, follow-up surveys were conducted that included basic demographic data, self-reported travel, and time spent in the forest over the past two weeks. Surveys are in the supplemental information; S1 was for village demographics at all timepoints, S2 was for detailed household and individual demographic information at T0, and S3 was for simpler information at T1. All survey instruments were developed in English, translated to Khmer, and field tested. Written Bunong language was recently developed and very few people can read or write the language, so when conducting surveys in this language the data collector verbally translated each question and recorded answers in Khmer. Surveys were conducted by staff of the Cambodia-based NGO Health Forefront Organization (HFO), a primary research partner for this program. Data were collected using Open Data Kit (ODK) with smartphones to limit data entry errors, and were uploaded to a cloud server daily. When data collection was complete, the database was downloaded onto password secured computers and analyzed by a member of the study team using Stata (StatCorp Version 14). Data were analyzed descriptively, with results stratified by target populations as these may have different risk profiles for malaria. Data was also analyzed by province, and where differences were found results were separated accordingly. For risk factors that were not expected to vary with time, such as demographic data and housing structure construction, data from all participants in T0 and all new participants in T1 were combined to reflect the backgrounds of all enrolled individuals. For time spent in the forest, data from T1 and T2 were analyzed separately as malaria incidence was expected to decrease throughout the study period. When each survey was conducted, RDTs for malaria were administered to participants who said they had a fever (temperature above 37 °C) during the survey. Dried blood spots were collected from all participants for later diagnosis using qPCR, which entailed extracting and amplifying DNA using a sensitive method that can detect infections below the detection limit of RDTs and microscopy [ 18 ]. Positive qPCR-detected infections were speciated, and the characteristics of infected individuals and their village of residence were analyzed, as well as self-reported travel patterns for those infected with P. falciparum malaria. Sample size calculation The final sample size implemented was based on requirements for the parent study looking at malaria prevalence at each timepoint following the distribution of various vector control tools and the number of the number of forest packs available and distributed. Overall at least 2,100 participants were included at each time point (total of 2935). Results An overview of villages, households, and individuals enrolled during the study is shown in Table 1 . Participant demographics are then described, followed by several risk factors for malaria including housing characteristics, time spent in the forest, and mosquito bite prevention tools used. Next, we summarize individual malaria history, cases identified using RDTs and qPCR, the locations of positive identified cases, and travel patterns for incident P. falciparum infections. Table 1 Overview of survey data collected at study timepoints Survey Level Survey timepoint Total T0 T1 T2 Village 16 2 * 0 18 Household 990 313 * 0 1,303 Individual Total 2,111 2,192 2,047 6,350 New enrolment 2,111 824 0 2,935 Survey conducted Baseline survey Follow-up survey Follow-up survey - * New villages and households enrolled at T1 Village demographics The villages enrolled for forest dwellers and goers are described below. A total of 18 villages were enrolled, with nine in Mondulkiri and nine in Kampong Speu province (Table 2 ). Villages in Mondulkiri had higher average numbers of households (199) and individuals (865) as compared to Kampong Speu, which had an average of 107 households and 375 individuals per village. For accessibility by car, this was lower in Mondulkiri, at 56%, as compared to 100% in Kampong Speu. Per inclusion criteria, all villages were accessible by motorcycle during the rainy season when the study took place. The number of Khrom, smaller clusters of households which are often separated from the main village but still included as part the village, was close to three per village for both provinces. Village data was not applicable to forest rangers, who were recruited from three ranger stations in Mondulkiri province. Table 2 Village summary data Village characteristic Location Mondulkiri Kampong Speu Villages enrolled 9 9 Number of households per village (average) 199 107 Village population (average) 875 374 Villages accessible by car during the rainy season? (%) 56% 100% Villages accessible by motorcycle during the rainy season? (%) 100% 100% Number of Khrom associated with village 2.8 3.2 Housing demographics Forest goers and dwellers enrolled at T0 were asked about their household amenities, and findings were similar between the two risk groups and provinces. For primary water source the most common answer as bottled water used in approximately 30% of households, almost half (47%) had flush toilets while approximately one third (34%) had no toilet, and more than half (61%) of households had electricity (table S1 ). Participant Demographics The study enrolled 2,935 individuals, including 1,093 (37%) forest goers, 1,787 (61%) forest dwellers, and 55 (2%) forest rangers (Table 3 ). Demographics were similar when comparing provinces, except that Mondulkiri Province had 59% of individuals of the Bunong ethnic group and 1% of other ethnicities while in Kampong Speu, all participants were Khmer (Table S2 ). The predominant ethnic group overall was Khmer, although approximately a third of forest goers and dwellers were Bunong, with a small number of participants in each group being from other minority ethnic groups. The majority of participants were ages 26–45, with an average age of 33. Forest goers and rangers were predominantly male (59% and 96%, respectively), whereas dwellers reflected a smaller proportion of males compared to females (41% males). For position in their household, the vast majority of rangers were head of household, as well as more than half of the forest goers enrolled. For those who were not head of household, approximately half of participants were adults who were the son or daughter of the head of household, and results were similar for each target group. Table 3 Participant demographics Characteristic n (%) Risk group (%) Forest Goer Forest Dweller Forest Ranger Basic demographic data collected on all new participants (T0 and T1) Total individuals n (%) 2,935 (100%) 1,093 (37%) 1,787 (61%) 55 (2%) Province Mondulkiri 1,510 (51%) 59 45 100 Kampong Speu 1,425 (49%) 41 55 0 Age 65 62 (2%) 2 3 0 Gender Male 1,434 (49%) 59 41 96 Female 1,493 (51%) 41 59 4 Other / not specified 4 (< 1%) < 1 0 0 Detailed demographic data collected from new participants at T0 only Total individuals n (%) 2,111 (100%) 730 (35%) 1,339 (63%) 42 (2%) Ethnic group Khmer 1,444 (68%) 70 67 81 Bunong 650 (31%) 28 33 17 Other 17 (1%) 2 < 1 2 Languages Khmer Understand spoken 2,100 (99%) 99 99 98 Speak fluently 2,014 (95%) 95 95 100 Reading 1,259 (60%) 55 61 100 Writing 1,210 (57%) 53 58 100 Bunong Understand spoken 753 (36%) 33 37 43 Speak fluently 673 (32%) 30 33 38 Reading 139 (7%) 4 8 7 Writing 107 (5%) 3 6 2 Household position Head of household 879 (42%) 54 34 91 Spouse of head (husband/wife) 434 (35%) 17 23 0 Child of head (son/daughter) 668 (54%) 24 36 5 Parent of head (father/mother) 26 (2%) 1 2 0 Other 104 (9%) 5 5 5 Participants enrolled at T0 were given a list of options on their sources of income. The main income sources reported by participants required spending time outside in the forest, with the most common income source being a farmer, which was represented by almost half of all participants (47%), including 26% of forest rangers who sometimes had more than one job (Table 4 ). For forest dwellers and rangers, other common sources of income included day labourers, which could include work in unskilled construction (e.g., rubber industry, rice mills), and forest collectors or foragers who gathered supplies from the forest. Table 4 Participant sources of income (T0) Income Sources* Total (%) Risk group (%) Forest Goer Forest Dweller Forest Ranger Total individuals 2,111 (100%) 730 (35%) 1,339 (63%) 42 (2%) Farmer 1,687 (47%) 85 79 26 Day labourer 644 (18%) 36 28 0 Forest collector / forager 578 (16%) 37 23 0 Logging 180 (5%) 17 4 0 Market Trader 149 (4%) 7 7 14 Unemployed 59 (2%) < 1 4 0 Driver / motorbike Taxi 11 (< 1%) 0 1 0 Retired 9 (< 1%) < 1 < 1 2 Handicrafts (basket weaving, etc.) 3 (< 1%) < 1 0 0 Other 200 (6%) 4 12 19 * Individuals may list more than one source of income Household amenities and structure openness Participants in all risk groups enrolled at T0 were asked about how open their living structures were, to determine their vulnerability to mosquito bites when spending time indoors. Primary living structures were similar across provinces (table S4 ) and across risk groups, with the majority of structures (71%) being closed with walls and a ceiling or roof (Table 5 ). The next most common answer (28%) were partially open structures with two to three walls and a ceiling. When asked whether participants had a secondary structure in the forest or farm, this was higher (57%) in Mondulkiri province as compared to Kampong Speu (20%) (table S3 ), and different between risk groups with most (95%) of forest rangers having a secondary structure, as compared to half (52%) of forest goers and 31% of forest dwellers. Most of these only had a ceiling (44%), posing risks of getting mosquito bites, with the next most common structure being enclosed (33%). Structure characteristics were similar when comparing risk groups. Table 5 Living structure characteristics (T0) Structure characteristics Total Risk group (%) Forest Goer Forest Dweller Forest Ranger Total individuals n (%) 2,111 (100%) 730 (35%) 1,339 (63%) 42 (2%) Primary living structure Enclosed room with walls and a ceiling or roof 71% 74 70 64 Ceiling and 2–3 walls 28% 25 30 36 Only ceiling < 1% 1 0 0 Completely open < 1% < 1 0 0 Secondary living structure Have secondary structure in forest or farm? 39% 52 31 95 Enclosed room with walls and a ceiling or roof 33% 25 44 3 Ceiling and 2–3 walls 5% 7 3 0 Only ceiling 44% 50 39 50 Completely open 17% 17 14 48 Time spent in the forest To understand the risk factors for getting malaria in the forest, participants at T0 were asked how often they go to the forest during the dry and rainy seasons. Results were similar in both provinces, with an average of approximately six days per week. This was approximately seven days a week for forest dwellers in both dry and rainy seasons (as they most often lived directly inside the forest), five to six days per week for forest goers with slightly higher frequency during the rainy season, and approximately five days a week for forest rangers. During follow-up surveys at T1 and T2, participants were asked how many days they spent in the forest in the past week (Table 6 ). Results were similar between provinces (table S5) and timepoints, with 85% of participants reporting going to the forest during the past week, with higher frequencies seen for forest rangers (98%) compared to forest dwellers (93%) and forest goers (71%). Those who went to the forest spent an average of 5 days in the forest every week, with 88% of forest dwellers reporting that they went to the forest daily, as compared to 59% of forest rangers and 34% of forest goers. Table 6 Time spent in the forest (T1 and T2) Time spent in the forest in past week Total (%) (n = 4,239) Risk group (%) Forest Goer (n = 1,522) Forest Dweller (n = 2,622) Forest Ranger (n = 95) Did not go to forest 632 (15%) 29% 7% 2% Went to forest every day 2,889 (68%) 34% 88% 59% Went to forest but not every day 716 (17%) 37% 5% 39% Average number of days* 5.1 5.2 4.4 6.4 *For those who went to the forest Baseline mosquito bite prevention tools used At T0, participants were asked about the mosquito bite prevention tools they used, not including the tools that were provided as part of the parent study after this survey. At a household level for forest dwellers and goers, almost all (97%) owned a bednet, most of which were treated with insecticides (79%) (Table 7 ). More than half (66%) of households enrolled also owned at least one hammock net of which most (84%) were treated with insecticides. Bednet and hammock ownership were very similar when comparing forest goers and dwellers. Table 7 Bednets and hammocks owned by households Tool ownership Total (n = 1,303) Risk group Forest Goer (n = 711) Forest Dweller (n = 592) Bednet Yes 97% 96.5% 97.5% How many 2.5 2.4 (range 0–10) 2.6 (range 1–10) Treated* 79% 74.8% 83.9% Hammock net Yes 66% 64.3% 68.4% How many 1.5 1.5 (range 1–5) 1.6 (range 0–9) Treated* 84% 81% 89% *Refers to treatment with insecticides (self reported) Participants at T0 were also asked about which mosquito bite prevention tools they used indoors or outdoors, during the day and night. Almost all participants reported using protective measures inside at night. When outside at night, protection was often used, especially for rangers (91%) as compared to forest dwellers (74%) and goers (66%). During the daytime, less protection from mosquito bites was used, with similar levels seen indoors and outdoors amongst all risk groups. Forest rangers had more than 80% protection outdoors, while dwellers had closer to 70% and goers around 55%. When asked about specific tools used at different times and locations, results were similar when comparing their use in villages (Fig. 2 ) and in the forest (Fig. 3 ) across all target groups. Sleeping under insecticide-treated nets was the most common method of protection, both indoors and outdoors at night, while wearing long sleeves in all circumstances except for being inside at night, when bednets were presumably preferred. The third most common method reported was burning coils. A Global Fund pack comprised of an insecticide-treated hammock net and topical repellent distributed by health workers and funded by the Global Fund to fight AIDS, Tuberculosis and Malaria. Travel patterns To understand general levels of mobility and travel, participants at T0 were asked how far they travel to buy necessities. Most participants reported having purchasing activities within the range of 500m from their primary residency location, especially forest dwellers. Forest rangers generally reported having a greater range of travel distance, with 45% of them reporting buying things from places located more than 5 km from their residency location (Table 8 ). Table 8 Travel patterns for purchasing necessities (T0) Distance travelled Total (n = 2,111) Risk group (%) Forest goers (n = 730) Forest dwellers (n = 1,339) Forest rangers (n = 42) Under 500 m 1,686 (80%) 79 84 19 500 m to 2 km 166 (8%) 11 5 33 2 to 5 km 75 (3%) 3 4 2 More than 5 km 184 (9%) 8 7 46 At T1 and T2, participants were asked whether they traveled to other villages. Only a small proportion of forest goers and dwellers (18 to 21%) reported traveling to other villages in the past 30 days (Table 9 ). This was a bit higher for forest rangers, 35 to 43% of whom reported traveling to other villages within that timeframe, where the area of their primary ranger station was defined as their home “village,” likely due to their work entailing travel throughout the forest. Participants were also asked about whether they had travel companions; almost all individuals traveled with people from the same villages. Travel patterns between timepoints was similar. Table 9 Travel to other villages during T1 and T2 Total (%) Risk group Forest goer Forest dweller Forest ranger Timepoint T1 T2 T1 T2 T1 T2 T1 T2 Total Individuals 2,192 2,047 801 721 1,345 1,277 46 49 Travel to another village in the past 30 days 400 (18%) 406 (20%) 143 (18%) 155 (21%) 237 (18%) 234 (18%) 20 (43%) 17 (35%) Travel companions People from the same village 1,858 (85%) 1,654 (81%) 610 (76%) 447 (62%) 1,228 (91%) 1,161 (91%) 20 (43%) 46 (94%) People from other villages 11 (< 1%) 5 (< 1%) 4 (< 1%) 4 (< 1%) 2 (< 1%) 1 (< 1%) 5 (11%) 0 (0%) People from the same and other villages 64 (3%) 15 (< 1%) 12 (1%) 5 (< 1%) 31 (2%) 9 (< 1%) 21(46%) 1 (2%) Malaria prevalence Malaria prevalence was assessed at each timepoint. RDTs were administered to participants who reported having an active fever, which was a total of 43 RDTs throughout the test period, all of which were negative. qPCR was conducted on dried blood spots collected from each participant at all three timepoints. This revealed a number of P. falciparum and P. vivax asymptomatic infections that are described sequentially below and mapped in supplemental Figs. 1 and 2. P. falciparum prevalence The prevalence of asymptomatic molecularly determined P. falciparum infections was similar at approximately 0.5% at both T0 and T1, which dropped to 0.2% in T2 which was an expected result due to declining malaria seasonality throughout the study period (Table 10 ). Prevalence was higher in Mondulkiri province as compared to Kampong Speu, with similar distribution between males and females. While a prevalence of P. falciparum of 4.8% was found in Forest Rangers at T0, no infections were subsequently found in this group. Forest goers and dwellers had roughly the same number of infections across all time points. Table 10 Plasmodium falciparum qPCR infections and their distribution Timepoint Total Province Gender* Risk group Mondulkiri Kampong Speu Males Females Forest Goer Forest Dweller Forest Ranger T0 n 2111 1104 1007 999 1108 730 1339 42 Pos (%) 11 (0.52%) 8 (0.72%) 3 (0.30%) 6 (0.60%) 5 (0.45%) 5 (0.68%) 4 (0.30%) 2 (4.76%) T1 n 2192 1113 1079 1020 1090 801 1345 46 Pos (%) 10 (0.46%) 9 (0.81%) 1 (0.09%) 6 (0.59%) 4 (0.37%) 4 (0.50%) 6 (0.45%) 0 (0%) T2 n 2047 1089 958 935 1026 721 1277 49 Pos (%) 3 (0.15%) 2 (0.18%) 1 (0.10%) 0 (0%) 3 (0.29%) 1 (0.14%) 2 (0.16%) 0 (0%) *T0: 4 individuals with unknown gender; T1: 82 individuals with unknown gender; T2: 87 individuals with unknown gender. 0 positives of unknown gender at all three timepoints. When investigating infection locations and travel patterns of infected individuals, P. falciparum infections were found to be clustered in villages in both provinces studied. In Mondulkiri province, 67% of cases were concentrated among forest dwellers in Pu Trom and Pu Nhav villages (Table 11 ). In Kampong Speu, 60% of P. falciparum cases were concentrated amongst forest dwellers in two villages as well, Banteay Roka and Banteay Roka Kirisenchey (M). Only three of the nine villages and two of three ranger stations enrolled in Mondulkiri province, and four of nine Kampong Speu villages included in the study had P. falciparum infections. Table 11 Residence locations of P. falciparum positive cases Province Residency location (village) Target Group Infections detected at T0 Mondulkiri Tu Trom Forest dweller Tu Trom Forest dweller D.A. Forest goer D.A. Forest goer D.A. Forest goer Pu Nhav Forest goer Ranger Station 1 Forest ranger Ranger Station 2 Forest ranger Kampong Speu Banteay Roka Kirisenchey (M) Forest dweller Banteay Roka Kirisenchey (M) Forest dweller Banteay Roka Kirisenchey (M) Forest goer Infections detected at T1 Mondulkiri Pu Khav Forest goer Pu Khav Forest goer Pu Khav Forest goer Pu Khav Forest goer Tu Trom Forest dweller Tu Trom Forest dweller Tu Trom Forest dweller Tu Trom Forest dweller Tu Trom Forest dweller Kampong Speu Banteay Roka Kirisenchey (M) Forest dweller Infections detected at T2 Mondulkiri Tu Trom Forest dweller Pu Nhav Forest goer Kampong Speu Doung Kraong Meanchey (M) Forest dweller When asked about travel history, none of the individuals with qPCR-positive P. falciparum infections reported traveling to other villages within 14 days of positive blood sample collection. In T0 no information was collected about travel to the forest, and this information was only available for some detected cases in T1 and T2, finding that individuals with asymptomatic P. falciparum malaria often traveled to the forest. Travel to villages was therefore not a risk factor amongst these cases, while going to the forest was associated with asymptomatic P. falciparum infection. P. vivax prevalence The prevalence of asymptomatic P. vivax infections detected by qPCR-positive infections was higher than for P. falciparum , with an overall prevalence of 4.1% that decreased throughout the study period (122 infections at T0, 78 at T1, and 61 at T2) (Table 12 ). When comparing between provinces, Kampong Speu had more P. vivax infections than Mondulkiri province, males had more infections than females, forest goers and dwellers had roughly the same prevalence of infection across all time points, and no P. vivax infections were found in forest rangers. When investigating locations of P. vivax infections, less clustering was observed as compared to P. falciparum cases. In Mondulkiri province, Pu Trom village, which had 42% of all P. falciparum cases in that province, accounted for 23% of all P. vivax cases. A large proportion of P. vivax cases were also identified in Andong Kraloeng (28%) and Pu Char (21%), with cases detected in all nine Mondulkiri villages included in the study. In Kampong Speu, the highest proportions of cases were found in Rumduol Thmei (27%) and Peam Lvea (21%) villages, with cases detected in all nine Kampong Speu villages included in the study. Table 12 Plasmodium vivax qPCR positive cases and their distribution Timepoint Total Province Gender* Risk group Mondulkiri Kampong Speu Males Females Forest Goer Forest Dweller Forest Ranger T0 n 2111 1104 1007 999 1108 730 1339 42 Pos (%) 122 (5.8%) 54 (4.9%) 68 (6.7%) 71 (7.1%) 51 (4.6%) 38 (5.2%) 84 (6.3%) 0 (0%) T1 n 2192 1113 1079 1020 1090 801 1345 46 Pos (%) 78 (3.6%) 22 (2.0%) 56 (5.2%) 49 (4.8%) 27 (2.5%) 34 (4.2%) 44 (3.3%) 0 (0%) T2 n 2047 1089 958 935 1026 721 1277 49 Pos (%) 61 (3.0%) 18 (1.7%) 43 (4.5%) 35 (3.7%) 23 (2.2%) 23 (3.2%) 38 (3.0%) 0 (0%) T0: 4 individuals and 9 positives with unknown gender; T1: 82 individuals and 2 positives with unknown gender; T2: 87 individuals and 3 positives with unknown gender. Discussion This large-scale serial cross-sectional study identified risk factors for malaria amongst forest-exposed populations in Mondulkiri Province and Kampong Speu Province, finding that in transmission foci in these provinces, participants often worked outdoors as farmers, day laborers, and forest collectors, some (28%) of whom also lived in open structures with two to three walls and a ceiling in their primary residence. Some participants (39%) also reported having a secondary structure they lived in, which was often open, 44% of which had only ceilings. The most common malaria prevention tools used were bednets, wearing long sleeves, and burning insecticide-treated coils. All infections detected during the study were asymptomatic, with clustering in villages observed for P. falciparum especially amongst forest dwellers, and no association between cases and self-reported travel to other villages. For P. vivax incidence was higher (4% as compared to < 1% for P. falciparum ), and infections were found in all enrolled villages among forest goers and dwellers, the latter who reported going to the forest more often than other risk groups, with 88% reporting spending time in the forest daily in follow-up surveys. For forest rangers, only two P. falciparum cases were detected from one ranger station at the baseline survey, and no P. vivax cases were detected. These findings can be applied directly to malaria elimination efforts in Cambodia. For P. falciparum , forest dwellers in villages where infections are found can be targeted for malaria interventions, including Pu Trom and Pu Nhav villages in Mondulkiri and Banteay Roka and Banteay Roka Kirisenchey (M) in Kampong Speu province. P. falciparum elimination will require that asymptomatic infections be addressed, a topic that will be discussed in a separate study that infers its prevalence through comparison with data from Cambodia’s malaria information system (MIS). P. vivax malaria was found in all study villages, revealing it is still a risk for forest goers and dwellers living in transmission foci. These findings suggest that in these locations, the prevention and treatment of infections can be targeted geographically, a result consistent with occupational and spatial clustering found in another study in Cambodia [ 12 ]. Geographical movement however did not present as a risk factor in this study, suggesting that travel between villages is not a major contributor of asymptomatic malaria transmission. In addition to the need to target forest dwellers and goers, this study also found that forest rangers, despite high amounts of time spent in the forest, had much lower malaria prevalence including no P. vivax infections found. This could be due to occupational health protective measures provided to rangers as shown by higher reported levels of protection from mosquito bites (80%) compared to other risk groups. Malaria elimination efforts in Cambodia can therefore target forest goers and dwellers in foci at the village level. When compared to other studies, these findings provide context to efforts to eliminate forest malaria in a variety of settings. An earlier study conducted in 17 villages in Mondulkiri Province from 2017–2018 showed higher levels of PCR-detectable infections, with an incidence of 6.4% for P. vivax and 3.0% for P. falciparum , approximately two to three times greater than that found in this study [ 12 ]. The earlier study also detected hotspots of infection in villages, finding that forest work was associated with malaria. These findings suggest that malaria incidence decreased in the study area since 2017, furthermore confirming that clusters of infection at a village level are a risk factor for malaria in these geographies. This study also provides further insights to those found in a pilot study earlier [ 14 ], showing that the use of bednets, wearing long sleeves, and insecticide-treated coils were the most common malaria prevention methods used, and that gaps in protection mostly take place during the day and outside at night. Targeting these high-risk populations of malaria can combine two approaches. The first is vector control; an evaluation of the distribution and use of forest packs including a topical repellent, a spatial repellent, and insecticide-treated clothes from the parent study is forthcoming and can further inform the selection of vector control tools that can be useful for these populations to prevent malaria. Hopefully forest pack components can overcome the limitations of wearing long sleeves, which was commonly reported in our study, especially when not sleeping indoors, as other Cambodian populations have reported that mosquitoes can bite through clothing [ 19 ]. A second approach is chemoprevention, where medicine can be distributed to forest-frequenting populations as intermittent preventive treatment or targeted drug administration to geographic hotspots [ 20 ]. This has shown to be effective for forest-going populations in Cambodia when targeting P. falciparum malaria [ 21 ], although clearing the dormant stages of P. vivax is expected to be more challenging [ 22 ]. This study had several limitations. It did not specifically include several risk profiles studied in Cambodia, such as illegal loggers [ 11 ] and mobile populations that create temporary forest encampments [ 19 ]. These risk profiles were studied several years ago however, and malaria endemicity in Cambodia has since decreased substantially, affirming our approach of intervening where malaria hotspots are identified from recently diagnosed cases. Detailed demographic data was not available for the 824 participants enrolled at T1 as these individuals were enrolled to meet sample size requirements. Although those enrolled at T1 represented approximately 30% of the study population, detailed demographic data on 2,111 participants was collected at T0, which we believe is sufficient to represent these at-risk populations in the village foci selected for inclusion. To support Cambodia’s goals to eliminate malaria, we recommend the immediate application of our findings to local malaria elimination strategies. Forest goers and dwellers should be targeted for prevention and treatment in hotspots where infections are detected. The vector control tools available to these high-risk populations can be expanded, with forthcoming reports on the parent study expected to inform the benefits and challenges on the delivery and uptake of topical repellents, spatial repellents, and insecticide-treated clothing in these locations. Declarations Ethics approval and consent to participate : The study protocol was approved by the University of California’s Human Research Protection Program Institutional Review Board (IRB 22-36956) and the Cambodia Ministry of Health National Ethics Committee for Health Research (NECHR 296). Informed consent was sought by each participant prior to enrollment. Competing interests : Study authors declare that they have no competing interests. Funding: This study is a component of Project BITE (Bite Interruption Toward Elimination), funded by the Australia Department of Foreign Affairs and Trade through the Innovative Vector Control Consortium (Grant number A134328). Research reported in this publication was supported by the National Institutes of Health under award number 5R03AI158800-02. IC is also supported through a Mentored Research Scientist Development Award (K01AI156182) funded by the National Institute for Health, National Institute of Allergy and Infectious Diseases. Author Contribution DM, DD, NL, and AT designed and led the study. DD led the implementation of the study, VK, PV, SP, VM, SB, KP, SC, KL, KH, and SS implemented the study. JT, DL, and JC analyzed laboratory samples and parasite movement data, DM analyzed survey data. IC, DM, DD, EV, AT, and NL interpreted the results. IC wrote the first draft of the manuscript. All authors reviewed the manuscript. Acknowledgement The authors are grateful to participants in this study. The authors also thank the Innovative Vector Control Consortium (IVCC) for the management of the grant which funded this work and for their technical collaboration and partnership. Data Availability Data is provided within the manuscript or supplementary information files. References WHO. Strategy for malaria elimination in the Greater Mekong Subregion: 2015–2030 2015 [ https://apps.who.int/iris/handle/10665/208203 Manzoni G, Try R, Guintran JO, Christiansen-Jucht C, Jacoby E, Sovannaroth S et al. Progress towards malaria elimination in the Greater Mekong Subregion: perspectives from the World Health Organization. Malar J. 2024;23(1). Xinhua. Cambodia records sharp drop in malaria cases in 2023: health official 2024 [ https://english.news.cn/20240112/895c5512d5d2416598f9895841cf39c5/c.html Nofal SD, Peto TJ, Adhikari B, Tripura R, Callery J, Bui TM et al. How can interventions that target forest-goers be tailored to accelerate malaria elimination in the Greater Mekong Subregion? A systematic review of the qualitative literature. Malar J. 2019;18(1). Ministry of Health C. The National Strategic Plan for Elimination of Malaria in the Kingdom of Cambodia 2011–2025. Health Mo, ed. Phnom Penh, Cambodia: Royal Government of Cambodia. 2011 [ http://www.cnm.gov.kh/userfiles/file/N%20Strategy%20Plan/National%20Strtegyin%20English.pdf WHO. Accelerating malaria elimination in the Greater Mekong 2022 [ https://www.who.int/publications/i/item/WHO-UCN-GMP-MME-2022.01 St Laurent B, Oy K, Miller B, Gasteiger EB, Lee E, Sovannaroth S, et al. Cow-baited tents are highly effective in sampling diverse Anopheles malaria vectors in Cambodia. Malar J. 2016;15(1):440. Vantaux A, Riehle MM, Piv E, Farley EJ, Chy S, Kim S et al. Anopheles ecology, genetics and malaria transmission in northern Cambodia. Sci Rep-Uk. 2021;11(1). Hewitt SE. Let’s ‘cut to the chase’ on malaria elimination in the Greater Mekong Subregion. Trans R Soc Trop Med Hyg. 2019;113(4):161–2. Chhim S, Piola P, Housen T, Herbreteau V, Tol B. Malaria in Cambodia: A Retrospective Analysis of a Changing Epidemiology 2006–2019. Int J Environ Res Public Health. 2021;18(4):1960. Bannister-Tyrrell M, Gryseels C, Sokha S, Dara L, Sereiboth N, James N, et al. Forest Goers and Multidrug-Resistant Malaria in Cambodia: An Ethnographic Study. The American Journal of Tropical Medicine and Hygiene; 2019. Sandfort M, Vantaux A, Kim S, Obadia T, Pepey A, Gardais S et al. Forest malaria in Cambodia: the occupational and spatial clustering of Plasmodium vivax and Plasmodium falciparum infection risk in a cross-sectional survey in Mondulkiri province, Cambodia. Malar J. 2020;19(1). Feachem RGA, Chen I, Akbari O, Bertozzi-Villa A, Bhatt S, Binka F, et al. Malaria eradication within a generation: ambitious, achievable, and necessary. Lancet. 2019;394(10203):1056–112. Chen I, Doum D, Mannion K, Hustedt J, Sovannaroth S, McIver D, et al. Applying the COM-B behaviour change model to a pilot study delivering volatile pyrethroid spatial repellents and insecticide-treated clothing to forest-exposed populations in Mondulkiri Province, Cambodia. Malar J. 2023;22(1):251. Vajda ÉA, Saeung M, Ross A, McIver DJ, Tatarsky A, Moore SJ et al. A semi-field evaluation in Thailand of the use of human landing catches (HLC) versus human-baited double net trap (HDN) for assessing the impact of a volatile pyrethroid spatial repellent and pyrethroid-treated clothing on Anopheles minimus landing. Malar J. 2023;22(1). Vontas J, Moore S, Kleinschmidt I, Ranson H, Lindsay S, Lengeler C, et al. Framework for rapid assessment and adoption of new vector control tools. Trends Parasitol. 2014;30(4):191–204. Guyant P, Canavati SE, Chea N, Ly P, Whittaker MA, Roca-Feltrer A et al. Malaria and the mobile and migrant population in Cambodia: a population movement framework to inform strategies for malaria control and elimination. Malar J. 2015;14(1). Holzschuh A, Koepfli C. Tenfold difference in DNA recovery rate: systematic comparison of whole blood vs. dried blood spot sample collection for malaria molecular surveillance. Malar J. 2022;21(1). Sanann N, Peto TJ, Tripura R, Callery JJ, Nguon C, Bui TM et al. Forest work and its implications for malaria elimination: a qualitative study. Malar J. 2019;18(1). Tripura R, Von Seidlein L, Sovannaroth S, Peto TJ, Callery JJ, Sokha M et al. Antimalarial chemoprophylaxis for forest goers in southeast Asia: an open-label, individually randomised controlled trial. Lancet Infect Dis. 2022. Iv S, Nguon C, Kong P, Sieng T, Srun S, Christiansen-Jucht C, et al. Intermittent preventive treatment for forest goers by forest malaria workers: an observational study on a key intervention for malaria elimination in Cambodia. Lancet Reg Health West Pac. 2024;47:101093. Aung PL, Soe MT, Soe TN, Oo TL, Win KM, Cui L et al. Factors hindering coverage of targeted mass treatment with primaquine in a malarious township of northern Myanmar in 2019–2020. Sci Rep-Uk. 2023;13(1). Additional Declarations No competing interests reported. Supplementary Files BITEP4Supplementaltablesandfigures.pdf SupplementalInfoS1VillagedemographicsT0andT1.pdf SupplementalinfoS2IndividualT0.pdf SupplementalInfoS3IndividualT1.pdf Cite Share Download PDF Status: Published Journal Publication published 22 Feb, 2025 Read the published version in Malaria Journal → Version 1 posted Editorial decision: Revision requested 20 Nov, 2024 Reviews received at journal 06 Nov, 2024 Reviews received at journal 04 Nov, 2024 Reviewers agreed at journal 28 Oct, 2024 Reviewers agreed at journal 28 Oct, 2024 Reviewers invited by journal 28 Oct, 2024 Editor assigned by journal 18 Oct, 2024 Submission checks completed at journal 18 Oct, 2024 First submitted to journal 18 Oct, 2024 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. 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survey","fulltext":[{"header":"Background","content":"\u003cp\u003eThe Greater Mekong Subregion has made tremendous progress towards its goal to eliminate human malaria by 2030 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This region has the highest prevalence of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e parasites that are resistant to artemisinin-class antimalarial drugs, and intensive efforts to eliminate this species of malaria regionally have contributed to a 97% reduction in malaria deaths, and 77% reduction in all malaria cases between 2012 and 2022 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Within this region, Cambodia, the epicenter of drug-resistant \u003cem\u003eP. falciparum\u003c/em\u003e parasites, is undergoing last mile efforts for elimination, with only 1,384 infections detected in 2023 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and no malaria-related deaths reported in country since 2017. Remaining infections are concentrated in remote locations in forested areas, often along international borders [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. To meet its goals to eliminate human malaria nationally by 2025 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], Cambodia will need to clear malaria infections among high-risk populations in highly forested locations where access to healthcare is poor [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and outdoor malaria transmission is common [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e This project is a part of a multi-stage study, Project Bite Interruption Towards Elimination (BITE), on novel mosquito bite prevention tools in a \u0026ldquo;forest pack\u0026rdquo; intended to guide the last mile efforts in Cambodia and potentially other locations challenged by outdoor malaria transmission. In earlier phases of the study a pilot study was conducted in Mondulkiri province investigating malaria risk factors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], the efficacy of insecticide treated clothing and spatial repellents to prevent mosquito bites [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and their acceptability among users [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Results were applied to this project, which is a large-scale risk factor assessment to characterize high-risk populations in Mondulkiri and Kampong Speu provinces. Villages included in this study are some of the highest incidence malaria settings remaining in Cambodia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], where malaria elimination efforts have been challenged by a high prevalence of outdoor-biting vectors including \u003cem\u003eAn. dirus, An. minimus\u003c/em\u003e, and \u003cem\u003eAn. maculatus\u003c/em\u003e mosquitoes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In addition to risk factor investigation this study includes malaria diagnosis data using rapid diagnostic tests (RDTs) and qPCR, providing insight on the nature of infections (symptomatic versus asymptomatic), whether they are geographically clustered, and whether human movement is a factor affecting transmission patterns. Additional outcomes from the parent study, including the rollout and user acceptability of mosquito bite prevention tools to this cohort, will be reported elsewhere.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a serial cross-sectional survey among forest-exposed individuals. Data was collected at three timepoints: October 2022 (Timepoint 0; T0) for baseline data collection, and two follow-up timepoints in December 2022 (T1), and February 2023 (T2). Due to loss to follow-up, additional participants were recruited in T1. Most risk factors were identified from the baseline survey for new participants recruited at T0, such as their demographics, housing structures, previous history of malaria infection, and malaria prevention tools in use prior to study initiation. New participants recruited in T1 had basic demographic data collected, and for some variables we used results collected in T1 and T2, for example time spent in the forest, to gain further insight on whether those risk factors changed throughout the malaria season. At all three timepoints, malaria diagnosis was also conducted using RDTs for febrile individuals and dried blood spots collected for all individuals for subsequent identification of parasite infection using qPCR [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. All positive cases identified were mapped to villages where participants resided, to check for clustering patterns. For \u003cem\u003eP. falciparum\u003c/em\u003e, travel patterns were investigated for potential associations between human movement and parasite incidence. This was not done for \u003cem\u003eP. vivax\u003c/em\u003e because incident infections could either be new ones or relapses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy location and population\u003c/h3\u003e\n\u003cp\u003eThis study took place in Mondulkiri Province and Kampong Speu Province, Cambodia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), where malaria peak case rates occur during the rainy season from August to January. The targeted study population included three high-risk populations for malaria: forest goers, forest dwellers, and forest rangers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], the first two of which were defined during the pilot phase of this study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Forest goers were individuals who lived at least 1 kilometer from the forest, traveling to the forest regularly for seasonal farming, hunting, or foraging (mushrooms, vegetables, and resin) or seasonal migration for gem mining, logging, and plantation work [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Forest dwellers survived on subsistence farming, living in the forest or within 1 kilometer of its fringes in a traditional house in a village for at least part of the year. Many forest dwellers also had a more open, temporary structure in the farm or forest that they migrated to during planting and harvesting seasons referred to as secondary living structures [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Forest rangers were recruited from Mondulkiri province only; they worked for government or wildlife and conservation agencies that protect the forest and areas near international borders, staying in ranger stations or outdoor hammocks up to 16 nights per month when they were on patrol [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVillages for the study were selected based on consultation with the Cambodian National Center for Parasitology, Entomology and Malaria Control (CNM), who identified locations with actively identified \u003cem\u003eP. falciparum\u003c/em\u003e foci that would likely benefit from receiving vector control forest packs for the parent study. \u0026ldquo;Village\u0026rdquo; refers to geographic regions that contain residential living structures or ranger stations in forested or non-forested locations, which were defined based on an administrative level within the Cambodian governmental system.\u003c/p\u003e\n\u003ch3\u003eInclusion Criteria\u003c/h3\u003e\n\u003cp\u003eIndividuals eligible for inclusion had to:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eReside in a village selected for the parent study, which required that they:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWere accessible by automobile or motorbike from September through January\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHad access to routine malaria data\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHad leaders with existing relationships with both the government and implementing partner\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMeet the definition of one of the three target populations at the time of enrollment:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eForest goer: lived outside the forest (more than 1 km from forest edge) with self-reported travel into the forest at least 15% of the time (approximately 1 day a week)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eForest dweller: lived in a village in the forest (or within 1 km of forest edge)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eForest ranger: actively conducted forest patrol activities and was based at a ranger station\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBe willing to meet study staff on a monthly basis for study follow-up activities, including meetings and the collection of finger prick blood samples for malaria testing.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBe age\u0026thinsp;\u0026ge;\u0026thinsp;3 years\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eProvide informed consent if aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, or obtain consent from guardian if participant is \u0026lt;\u0026thinsp;18 years of age\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSpeak Khmer and/or Bunong language\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eRecruitment\u003c/h3\u003e\n\u003cp\u003eIndividuals from the three target populations were recruited using different methods. For forest goers and dwellers, the study team worked closely with the local government, implementing partners, village chiefs, and other influential members of the communities, to gain support for the study and determine the best methods for participant recruitment. To recruit forest rangers, our study team partnered with the Wildlife Conservation Society (WCS), engaging with manager-level forest rangers in three ranger stations in Mondulkiri province only, because there were very few ranger stations operating in Kampong Speu.\u003c/p\u003e \u003cp\u003eWhen recruiting prospective participants, the study team introduced themselves and checked if individuals met the study inclusion criteria. Those eligible and interested to partake in the study were provided with detailed information about the study including the purpose of the project, potential risks and benefits of participation, project duration, and expectations of participants for the study. The study team emphasized that individuals could refuse enrolment in the study or remove themselves from the study at any time without repercussion. After these details were provided, informed consent was sought in Khmer or Bunong. Those able to read were given the informed consent form, and those unable to read had the form read aloud to them. Those who provided informed consent were then enrolled in the study. Eligible individuals from each village were recruited until the target number of participants was reached.\u003c/p\u003e\n\u003ch3\u003eData collection and analysis\u003c/h3\u003e\n\u003cp\u003eAt T0, a survey questionnaire was administered to all participants capturing village, household, and individual-level demographic information, housing construction, and use of vector control tools at baseline. At T1 and T2, follow-up surveys were conducted that included basic demographic data, self-reported travel, and time spent in the forest over the past two weeks. Surveys are in the supplemental information; S1 was for village demographics at all timepoints, S2 was for detailed household and individual demographic information at T0, and S3 was for simpler information at T1. All survey instruments were developed in English, translated to Khmer, and field tested. Written Bunong language was recently developed and very few people can read or write the language, so when conducting surveys in this language the data collector verbally translated each question and recorded answers in Khmer.\u003c/p\u003e \u003cp\u003eSurveys were conducted by staff of the Cambodia-based NGO Health Forefront Organization (HFO), a primary research partner for this program. Data were collected using Open Data Kit (ODK) with smartphones to limit data entry errors, and were uploaded to a cloud server daily. When data collection was complete, the database was downloaded onto password secured computers and analyzed by a member of the study team using Stata (StatCorp Version 14).\u003c/p\u003e \u003cp\u003eData were analyzed descriptively, with results stratified by target populations as these may have different risk profiles for malaria. Data was also analyzed by province, and where differences were found results were separated accordingly. For risk factors that were not expected to vary with time, such as demographic data and housing structure construction, data from all participants in T0 and all new participants in T1 were combined to reflect the backgrounds of all enrolled individuals. For time spent in the forest, data from T1 and T2 were analyzed separately as malaria incidence was expected to decrease throughout the study period.\u003c/p\u003e \u003cp\u003eWhen each survey was conducted, RDTs for malaria were administered to participants who said they had a fever (temperature above 37 \u0026deg;C) during the survey. Dried blood spots were collected from all participants for later diagnosis using qPCR, which entailed extracting and amplifying DNA using a sensitive method that can detect infections below the detection limit of RDTs and microscopy [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Positive qPCR-detected infections were speciated, and the characteristics of infected individuals and their village of residence were analyzed, as well as self-reported travel patterns for those infected with \u003cem\u003eP. falciparum\u003c/em\u003e malaria.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample size calculation\u003c/h2\u003e \u003cp\u003eThe final sample size implemented was based on requirements for the parent study looking at malaria prevalence at each timepoint following the distribution of various vector control tools and the number of the number of forest packs available and distributed. Overall at least 2,100 participants were included at each time point (total of 2935).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAn overview of villages, households, and individuals enrolled during the study is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Participant demographics are then described, followed by several risk factors for malaria including housing characteristics, time spent in the forest, and mosquito bite prevention tools used. Next, we summarize individual malaria history, cases identified using RDTs and qPCR, the locations of positive identified cases, and travel patterns for incident \u003cem\u003eP. falciparum\u003c/em\u003e infections.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverview of survey data collected at study timepoints\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eSurvey Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eSurvey timepoint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eT0\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVillage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHousehold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e313\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndividual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNew enrolment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSurvey conducted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFollow-up survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFollow-up survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003eNew villages and households enrolled at T1\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eVillage demographics\u003c/h3\u003e\n\u003cp\u003eThe villages enrolled for forest dwellers and goers are described below. A total of 18 villages were enrolled, with nine in Mondulkiri and nine in Kampong Speu province (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Villages in Mondulkiri had higher average numbers of households (199) and individuals (865) as compared to Kampong Speu, which had an average of 107 households and 375 individuals per village. For accessibility by car, this was lower in Mondulkiri, at 56%, as compared to 100% in Kampong Speu. Per inclusion criteria, all villages were accessible by motorcycle during the rainy season when the study took place. The number of Khrom, smaller clusters of households which are often separated from the main village but still included as part the village, was close to three per village for both provinces. Village data was not applicable to forest rangers, who were recruited from three ranger stations in Mondulkiri province.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVillage summary data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVillage characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMondulkiri\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKampong Speu\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillages enrolled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of households per village (average)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillage population (average)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillages accessible by car during the rainy season? (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillages accessible by motorcycle during the rainy season? (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Khrom associated with village\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHousing demographics\u003c/h2\u003e \u003cp\u003eForest goers and dwellers enrolled at T0 were asked about their household amenities, and findings were similar between the two risk groups and provinces. For primary water source the most common answer as bottled water used in approximately 30% of households, almost half (47%) had flush toilets while approximately one third (34%) had no toilet, and more than half (61%) of households had electricity (table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Demographics\u003c/h2\u003e \u003cp\u003eThe study enrolled 2,935 individuals, including 1,093 (37%) forest goers, 1,787 (61%) forest dwellers, and 55 (2%) forest rangers (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Demographics were similar when comparing provinces, except that Mondulkiri Province had 59% of individuals of the Bunong ethnic group and 1% of other ethnicities while in Kampong Speu, all participants were Khmer (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The predominant ethnic group overall was Khmer, although approximately a third of forest goers and dwellers were Bunong, with a small number of participants in each group being from other minority ethnic groups. The majority of participants were ages 26\u0026ndash;45, with an average age of 33. Forest goers and rangers were predominantly male (59% and 96%, respectively), whereas dwellers reflected a smaller proportion of males compared to females (41% males). For position in their household, the vast majority of rangers were head of household, as well as more than half of the forest goers enrolled. For those who were not head of household, approximately half of participants were adults who were the son or daughter of the head of household, and results were similar for each target group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c3\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eRisk group (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eForest Goer\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eForest Dweller\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eForest Ranger\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBasic demographic data collected on all new participants (T0 and T1)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,935 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,093 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,787 (61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMondulkiri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,510 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKampong Speu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,425 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e517 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e540 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,253 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u0026ndash;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e563 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,434 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,493 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther / not specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDetailed demographic data collected from new participants at T0 only\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,111 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e730 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,339 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eEthnic group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKhmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,444 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBunong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e650 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eLanguages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eKhmer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderstand spoken\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,100 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeak fluently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,014 (95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,259 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWriting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,210 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eBunong\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderstand spoken\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e753 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeak fluently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e673 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWriting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003eHousehold position\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHead of household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e879 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpouse of head (husband/wife)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e434 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChild of head (son/daughter)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e668 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParent of head (father/mother)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants enrolled at T0 were given a list of options on their sources of income. The main income sources reported by participants required spending time outside in the forest, with the most common income source being a farmer, which was represented by almost half of all participants (47%), including 26% of forest rangers who sometimes had more than one job (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For forest dwellers and rangers, other common sources of income included day labourers, which could include work in unskilled construction (e.g., rubber industry, rice mills), and forest collectors or foragers who gathered supplies from the forest.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant sources of income (T0)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIncome Sources*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eRisk group (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eForest\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eGoer\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eForest\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eDweller\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eForest\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eRanger\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,111 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,339 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,687 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay labourer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e644 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForest collector / forager\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e578 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLogging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarket Trader\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDriver / motorbike Taxi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandicrafts (basket weaving, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003eIndividuals may list more than one source of income\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHousehold amenities and structure openness\u003c/h2\u003e \u003cp\u003eParticipants in all risk groups enrolled at T0 were asked about how open their living structures were, to determine their vulnerability to mosquito bites when spending time indoors. Primary living structures were similar across provinces (table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e) and across risk groups, with the majority of structures (71%) being closed with walls and a ceiling or roof (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The next most common answer (28%) were partially open structures with two to three walls and a ceiling. When asked whether participants had a secondary structure in the forest or farm, this was higher (57%) in Mondulkiri province as compared to Kampong Speu (20%) (table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e), and different between risk groups with most (95%) of forest rangers having a secondary structure, as compared to half (52%) of forest goers and 31% of forest dwellers. Most of these only had a ceiling (44%), posing risks of getting mosquito bites, with the next most common structure being enclosed (33%). Structure characteristics were similar when comparing risk groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLiving structure characteristics (T0)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStructure characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eRisk group (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest Goer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForest Dweller\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eForest Ranger\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal individuals n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,111 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,339 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary living structure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnclosed room with walls and a ceiling or roof\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCeiling and 2\u0026ndash;3 walls\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOnly ceiling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCompletely open\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecondary living structure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHave secondary structure in forest or farm?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnclosed room with walls and a ceiling or roof\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCeiling and 2\u0026ndash;3 walls\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOnly ceiling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCompletely open\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTime spent in the forest\u003c/h2\u003e \u003cp\u003eTo understand the risk factors for getting malaria in the forest, participants at T0 were asked how often they go to the forest during the dry and rainy seasons. Results were similar in both provinces, with an average of approximately six days per week. This was approximately seven days a week for forest dwellers in both dry and rainy seasons (as they most often lived directly inside the forest), five to six days per week for forest goers with slightly higher frequency during the rainy season, and approximately five days a week for forest rangers.\u003c/p\u003e \u003cp\u003eDuring follow-up surveys at T1 and T2, participants were asked how many days they spent in the forest in the past week (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Results were similar between provinces (table S5) and timepoints, with 85% of participants reporting going to the forest during the past week, with higher frequencies seen for forest rangers (98%) compared to forest dwellers (93%) and forest goers (71%). Those who went to the forest spent an average of 5 days in the forest every week, with 88% of forest dwellers reporting that they went to the forest daily, as compared to 59% of forest rangers and 34% of forest goers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTime spent in the forest (T1 and T2)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime spent in the forest in past week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (%)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;4,239)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eRisk group (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eForest Goer (n\u0026thinsp;=\u0026thinsp;1,522)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eForest Dweller (n\u0026thinsp;=\u0026thinsp;2,622)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eForest Ranger (n\u0026thinsp;=\u0026thinsp;95)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not go to forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e632 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent to forest every day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,889 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent to forest but not every day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e716 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage number of days*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*For those who went to the forest\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eBaseline mosquito bite prevention tools used\u003c/h2\u003e \u003cp\u003eAt T0, participants were asked about the mosquito bite prevention tools they used, not including the tools that were provided as part of the parent study after this survey. At a household level for forest dwellers and goers, almost all (97%) owned a bednet, most of which were treated with insecticides (79%) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). More than half (66%) of households enrolled also owned at least one hammock net of which most (84%) were treated with insecticides. Bednet and hammock ownership were very similar when comparing forest goers and dwellers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBednets and hammocks owned by households\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTool ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;1,303)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRisk group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForest Goer (n\u0026thinsp;=\u0026thinsp;711)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eForest Dweller (n\u0026thinsp;=\u0026thinsp;592)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBednet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow many\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (range 0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6 (range 1\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreated*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHammock net\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow many\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5 (range 1\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6 (range 0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreated*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Refers to treatment with insecticides (self reported)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants at T0 were also asked about which mosquito bite prevention tools they used indoors or outdoors, during the day and night. Almost all participants reported using protective measures inside at night. When outside at night, protection was often used, especially for rangers (91%) as compared to forest dwellers (74%) and goers (66%). During the daytime, less protection from mosquito bites was used, with similar levels seen indoors and outdoors amongst all risk groups. Forest rangers had more than 80% protection outdoors, while dwellers had closer to 70% and goers around 55%.\u003c/p\u003e \u003cp\u003eWhen asked about specific tools used at different times and locations, results were similar when comparing their use in villages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and in the forest (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) across all target groups. Sleeping under insecticide-treated nets was the most common method of protection, both indoors and outdoors at night, while wearing long sleeves in all circumstances except for being inside at night, when bednets were presumably preferred. The third most common method reported was burning coils. A Global Fund pack comprised of an insecticide-treated hammock net and topical repellent distributed by health workers and funded by the Global Fund to fight AIDS, Tuberculosis and Malaria.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTravel patterns\u003c/h2\u003e \u003cp\u003eTo understand general levels of mobility and travel, participants at T0 were asked how far they travel to buy necessities. Most participants reported having purchasing activities within the range of 500m from their primary residency location, especially forest dwellers. Forest rangers generally reported having a greater range of travel distance, with 45% of them reporting buying things from places located more than 5 km from their residency location (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTravel patterns for purchasing necessities (T0)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDistance travelled\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;2,111)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eRisk group (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goers (n\u0026thinsp;=\u0026thinsp;730)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForest dwellers (n\u0026thinsp;=\u0026thinsp;1,339)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eForest rangers (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder 500 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,686 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e500 m to 2 km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 to 5 km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 5 km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt T1 and T2, participants were asked whether they traveled to other villages. Only a small proportion of forest goers and dwellers (18 to 21%) reported traveling to other villages in the past 30 days (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). This was a bit higher for forest rangers, 35 to 43% of whom reported traveling to other villages within that timeframe, where the area of their primary ranger station was defined as their home \u0026ldquo;village,\u0026rdquo; likely due to their work entailing travel throughout the forest. Participants were also asked about whether they had travel companions; almost all individuals traveled with people from the same villages. Travel patterns between timepoints was similar.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTravel to other villages during T1 and T2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c4\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003eTotal (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c10\" namest=\"c5\"\u003e \u003cp\u003eRisk group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003eForest goer\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eForest dweller\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cb\u003eForest ranger\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTimepoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2,192\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2,047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e801\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e721\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1,345\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1,277\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTravel to another village in the past 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e406 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e155 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e237 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e234 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17 (35%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTravel companions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePeople from the\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003esame village\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,858 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,654 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e610 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e447 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,228 (91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,161 (91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46 (94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePeople from\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eother villages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePeople from the\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003esame and other\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003evillages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (\u0026lt;\u0026thinsp;1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21(46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMalaria prevalence\u003c/h2\u003e \u003cp\u003eMalaria prevalence was assessed at each timepoint. RDTs were administered to participants who reported having an active fever, which was a total of 43 RDTs throughout the test period, all of which were negative. qPCR was conducted on dried blood spots collected from each participant at all three timepoints. This revealed a number of \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e asymptomatic infections that are described sequentially below and mapped in supplemental Figs.\u0026nbsp;1 and 2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eP. falciparum prevalence\u003c/h2\u003e \u003cp\u003eThe prevalence of asymptomatic molecularly determined \u003cem\u003eP. falciparum\u003c/em\u003e infections was similar at approximately 0.5% at both T0 and T1, which dropped to 0.2% in T2 which was an expected result due to declining malaria seasonality throughout the study period (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Prevalence was higher in Mondulkiri province as compared to Kampong Speu, with similar distribution between males and females. While a prevalence of \u003cem\u003eP. falciparum\u003c/em\u003e of 4.8% was found in Forest Rangers at T0, no infections were subsequently found in this group. Forest goers and dwellers had roughly the same number of infections across all time points.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003ePlasmodium falciparum\u003c/b\u003e \u003cb\u003eqPCR\u003c/b\u003e \u003cb\u003einfections and their distribution\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTimepoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eGender*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eRisk group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMondulkiri\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eKampong Speu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eFemales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eForest Goer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eForest Dweller\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eForest Ranger\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(0.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e(0.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (0.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (0.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (0.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4 (0.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2 (4.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (0.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003cp\u003e(0.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e(0.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (0.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (0.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (0.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6 (0.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e(0.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e(0.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e(0.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (0.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (0.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (0.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e(0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*T0: 4 individuals with unknown gender; T1: 82 individuals with unknown gender; T2: 87 individuals with unknown gender. 0 positives of unknown gender at all three timepoints.\u003c/p\u003e \u003cp\u003eWhen investigating infection locations and travel patterns of infected individuals, \u003cem\u003eP. falciparum\u003c/em\u003e infections were found to be clustered in villages in both provinces studied. In Mondulkiri province, 67% of cases were concentrated among forest dwellers in Pu Trom and Pu Nhav villages (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). In Kampong Speu, 60% of \u003cem\u003eP. falciparum\u003c/em\u003e cases were concentrated amongst forest dwellers in two villages as well, Banteay Roka and Banteay Roka Kirisenchey (M). Only three of the nine villages and two of three ranger stations enrolled in Mondulkiri province, and four of nine Kampong Speu villages included in the study had \u003cem\u003eP. falciparum\u003c/em\u003e infections.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResidence locations of P. falciparum positive cases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidency location (village)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTarget Group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInfections detected at T0\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eMondulkiri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.A.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.A.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.A.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Nhav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRanger Station 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest ranger\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRanger Station 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest ranger\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eKampong Speu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanteay Roka Kirisenchey (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanteay Roka Kirisenchey (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanteay Roka Kirisenchey (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInfections detected at T1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eMondulkiri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Khav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Khav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Khav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Khav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKampong Speu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanteay Roka Kirisenchey (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInfections detected at T2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMondulkiri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTu Trom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePu Nhav\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest goer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKampong Speu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoung Kraong Meanchey (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest dweller\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen asked about travel history, none of the individuals with qPCR-positive \u003cem\u003eP. falciparum\u003c/em\u003e infections reported traveling to other villages within 14 days of positive blood sample collection. In T0 no information was collected about travel to the forest, and this information was only available for some detected cases in T1 and T2, finding that individuals with asymptomatic \u003cem\u003eP. falciparum\u003c/em\u003e malaria often traveled to the forest. Travel to villages was therefore not a risk factor amongst these cases, while going to the forest was associated with asymptomatic \u003cem\u003eP. falciparum\u003c/em\u003e infection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eP. vivax prevalence\u003c/h2\u003e \u003cp\u003eThe prevalence of asymptomatic \u003cem\u003eP. vivax\u003c/em\u003e infections detected by qPCR-positive infections was higher than for \u003cem\u003eP. falciparum\u003c/em\u003e, with an overall prevalence of 4.1% that decreased throughout the study period (122 infections at T0, 78 at T1, and 61 at T2) (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). When comparing between provinces, Kampong Speu had more \u003cem\u003eP. vivax\u003c/em\u003e infections than Mondulkiri province, males had more infections than females, forest goers and dwellers had roughly the same prevalence of infection across all time points, and no \u003cem\u003eP. vivax\u003c/em\u003e infections were found in forest rangers.\u003c/p\u003e \u003cp\u003eWhen investigating locations of \u003cem\u003eP. vivax\u003c/em\u003e infections, less clustering was observed as compared to \u003cem\u003eP. falciparum\u003c/em\u003e cases. In Mondulkiri province, Pu Trom village, which had 42% of all \u003cem\u003eP. falciparum\u003c/em\u003e cases in that province, accounted for 23% of all \u003cem\u003eP. vivax\u003c/em\u003e cases. A large proportion of \u003cem\u003eP. vivax\u003c/em\u003e cases were also identified in Andong Kraloeng (28%) and Pu Char (21%), with cases detected in all nine Mondulkiri villages included in the study. In Kampong Speu, the highest proportions of cases were found in Rumduol Thmei (27%) and Peam Lvea (21%) villages, with cases detected in all nine Kampong Speu villages included in the study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003ePlasmodium vivax\u003c/b\u003e \u003cb\u003eqPCR\u003c/b\u003e \u003cb\u003epositive cases and their distribution\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTimepoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eGender*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eRisk group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMondulkiri\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eKampong Speu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eFemales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eForest Goer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eForest Dweller\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eForest Ranger\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e84 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e44 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePos (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eT0: 4 individuals and 9 positives with unknown gender; T1: 82 individuals and 2 positives with unknown gender; T2: 87 individuals and 3 positives with unknown gender.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis large-scale serial cross-sectional study identified risk factors for malaria amongst forest-exposed populations in Mondulkiri Province and Kampong Speu Province, finding that in transmission foci in these provinces, participants often worked outdoors as farmers, day laborers, and forest collectors, some (28%) of whom also lived in open structures with two to three walls and a ceiling in their primary residence. Some participants (39%) also reported having a secondary structure they lived in, which was often open, 44% of which had only ceilings. The most common malaria prevention tools used were bednets, wearing long sleeves, and burning insecticide-treated coils. All infections detected during the study were asymptomatic, with clustering in villages observed for \u003cem\u003eP. falciparum\u003c/em\u003e especially amongst forest dwellers, and no association between cases and self-reported travel to other villages. For \u003cem\u003eP. vivax\u003c/em\u003e incidence was higher (4% as compared to \u0026lt;\u0026thinsp;1% for \u003cem\u003eP. falciparum\u003c/em\u003e), and infections were found in all enrolled villages among forest goers and dwellers, the latter who reported going to the forest more often than other risk groups, with 88% reporting spending time in the forest daily in follow-up surveys. For forest rangers, only two \u003cem\u003eP. falciparum\u003c/em\u003e cases were detected from one ranger station at the baseline survey, and no \u003cem\u003eP. vivax\u003c/em\u003e cases were detected.\u003c/p\u003e \u003cp\u003eThese findings can be applied directly to malaria elimination efforts in Cambodia. For \u003cem\u003eP. falciparum\u003c/em\u003e, forest dwellers in villages where infections are found can be targeted for malaria interventions, including Pu Trom and Pu Nhav villages in Mondulkiri and Banteay Roka and Banteay Roka Kirisenchey (M) in Kampong Speu province. \u003cem\u003eP. falciparum\u003c/em\u003e elimination will require that asymptomatic infections be addressed, a topic that will be discussed in a separate study that infers its prevalence through comparison with data from Cambodia\u0026rsquo;s malaria information system (MIS). \u003cem\u003eP. vivax\u003c/em\u003e malaria was found in all study villages, revealing it is still a risk for forest goers and dwellers living in transmission foci. These findings suggest that in these locations, the prevention and treatment of infections can be targeted geographically, a result consistent with occupational and spatial clustering found in another study in Cambodia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Geographical movement however did not present as a risk factor in this study, suggesting that travel between villages is not a major contributor of asymptomatic malaria transmission. In addition to the need to target forest dwellers and goers, this study also found that forest rangers, despite high amounts of time spent in the forest, had much lower malaria prevalence including no \u003cem\u003eP. vivax\u003c/em\u003e infections found. This could be due to occupational health protective measures provided to rangers as shown by higher reported levels of protection from mosquito bites (80%) compared to other risk groups. Malaria elimination efforts in Cambodia can therefore target forest goers and dwellers in foci at the village level.\u003c/p\u003e \u003cp\u003eWhen compared to other studies, these findings provide context to efforts to eliminate forest malaria in a variety of settings. An earlier study conducted in 17 villages in Mondulkiri Province from 2017\u0026ndash;2018 showed higher levels of PCR-detectable infections, with an incidence of 6.4% for \u003cem\u003eP. vivax\u003c/em\u003e and 3.0% for \u003cem\u003eP. falciparum\u003c/em\u003e, approximately two to three times greater than that found in this study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The earlier study also detected hotspots of infection in villages, finding that forest work was associated with malaria. These findings suggest that malaria incidence decreased in the study area since 2017, furthermore confirming that clusters of infection at a village level are a risk factor for malaria in these geographies. This study also provides further insights to those found in a pilot study earlier [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], showing that the use of bednets, wearing long sleeves, and insecticide-treated coils were the most common malaria prevention methods used, and that gaps in protection mostly take place during the day and outside at night.\u003c/p\u003e \u003cp\u003eTargeting these high-risk populations of malaria can combine two approaches. The first is vector control; an evaluation of the distribution and use of forest packs including a topical repellent, a spatial repellent, and insecticide-treated clothes from the parent study is forthcoming and can further inform the selection of vector control tools that can be useful for these populations to prevent malaria. Hopefully forest pack components can overcome the limitations of wearing long sleeves, which was commonly reported in our study, especially when not sleeping indoors, as other Cambodian populations have reported that mosquitoes can bite through clothing [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A second approach is chemoprevention, where medicine can be distributed to forest-frequenting populations as intermittent preventive treatment or targeted drug administration to geographic hotspots [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This has shown to be effective for forest-going populations in Cambodia when targeting \u003cem\u003eP. falciparum\u003c/em\u003e malaria [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], although clearing the dormant stages of \u003cem\u003eP. vivax\u003c/em\u003e is expected to be more challenging [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study had several limitations. It did not specifically include several risk profiles studied in Cambodia, such as illegal loggers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and mobile populations that create temporary forest encampments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These risk profiles were studied several years ago however, and malaria endemicity in Cambodia has since decreased substantially, affirming our approach of intervening where malaria hotspots are identified from recently diagnosed cases. Detailed demographic data was not available for the 824 participants enrolled at T1 as these individuals were enrolled to meet sample size requirements. Although those enrolled at T1 represented approximately 30% of the study population, detailed demographic data on 2,111 participants was collected at T0, which we believe is sufficient to represent these at-risk populations in the village foci selected for inclusion.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo support Cambodia\u0026rsquo;s goals to eliminate malaria, we recommend the immediate application of our findings to local malaria elimination strategies. Forest goers and dwellers should be targeted for prevention and treatment in hotspots where infections are detected. The vector control tools available to these high-risk populations can be expanded, with forthcoming reports on the parent study expected to inform the benefits and challenges on the delivery and uptake of topical repellents, spatial repellents, and insecticide-treated clothing in these locations.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003e \u003cb\u003eEthics approval and consent to participate\u003c/b\u003e:\u003c/strong\u003e \u003cp\u003e The study protocol was approved by the University of California\u0026rsquo;s Human Research Protection Program Institutional Review Board (IRB 22-36956) and the Cambodia Ministry of Health National Ethics Committee for Health Research (NECHR 296). Informed consent was sought by each participant prior to enrollment.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003e Competing interests\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eStudy authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study is a component of Project BITE (Bite Interruption Toward Elimination), funded by the Australia Department of Foreign Affairs and Trade through the Innovative Vector Control Consortium (Grant number A134328). Research reported in this publication was supported by the National Institutes of Health under award number 5R03AI158800-02. IC is also supported through a Mentored Research Scientist Development Award (K01AI156182) funded by the National Institute for Health, National Institute of Allergy and Infectious Diseases.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDM, DD, NL, and AT designed and led the study. DD led the implementation of the study, VK, PV, SP, VM, SB, KP, SC, KL, KH, and SS implemented the study. JT, DL, and JC analyzed laboratory samples and parasite movement data, DM analyzed survey data. IC, DM, DD, EV, AT, and NL interpreted the results. IC wrote the first draft of the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors are grateful to participants in this study. The authors also thank the Innovative Vector Control Consortium (IVCC) for the management of the grant which funded this work and for their technical collaboration and partnership.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. 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Tenfold difference in DNA recovery rate: systematic comparison of whole blood vs. dried blood spot sample collection for malaria molecular surveillance. Malar J. 2022;21(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanann N, Peto TJ, Tripura R, Callery JJ, Nguon C, Bui TM et al. Forest work and its implications for malaria elimination: a qualitative study. Malar J. 2019;18(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTripura R, Von Seidlein L, Sovannaroth S, Peto TJ, Callery JJ, Sokha M et al. Antimalarial chemoprophylaxis for forest goers in southeast Asia: an open-label, individually randomised controlled trial. Lancet Infect Dis. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIv S, Nguon C, Kong P, Sieng T, Srun S, Christiansen-Jucht C, et al. Intermittent preventive treatment for forest goers by forest malaria workers: an observational study on a key intervention for malaria elimination in Cambodia. Lancet Reg Health West Pac. 2024;47:101093.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAung PL, Soe MT, Soe TN, Oo TL, Win KM, Cui L et al. Factors hindering coverage of targeted mass treatment with primaquine in a malarious township of northern Myanmar in 2019\u0026ndash;2020. Sci Rep-Uk. 2023;13(1).\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"malaria, malaria elimination, vulnerable population, forest malaria, forest dweller, vector control, mosquito, volatile pyrethroid, spatial repellent, insecticide-treated clothing","lastPublishedDoi":"10.21203/rs.3.rs-5291817/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5291817/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background: Cambodia strives to eliminate all species of human malaria by 2025, requiring that foci among forest-exposed populations in remote settings be addressed. This study explores malaria risk factors amongst forest-exposed groups in Mondulkiri and Kampong Speu Provinces, Cambodia as part of a multi-stage study on novel bite prevention tools (Project BITE).\nMethods: A serial cross-sectional survey explored the demographics, housing structure openness, mosquito bite prevention habits, and gaps in protection amongst three target groups: forest goers who work in the forest, forest dwellers who live in the forest, and forest rangers who patrol forested regions. Malaria prevalence data was collected at three time points using rapid diagnostic tests (RDTs) for febrile individuals and qPCR for all participants. Infection locations and travel patterns of P. falciparum-infected individuals were analyzed for clustering and the potential movement of infections.\nResults: 2,935 participants were enrolled between October 2022 and February 2023, consisting of 1,093 (37%) forest goers and 1,787 (61%) forest dwellers across both provinces, and 55 (5%) forest rangers in Mondulkiri province. Most worked outdoors as farmers, day laborers, and forest collectors, and reported going to the forest five to seven days a week. For housing, 29% and 39% of participants reported living in partially open primary and secondary structures, respectively. The main methods of mosquito bite protection used were insecticide-treated nets, wearing long sleeves, and burning mosquito coils, with gaps in protection during the daytime and outside at night. All febrile individuals had negative RDT test results. For qPCR, 24 P. falciparum infections (\u003c1%) were detected among forest goers and dwellers, clustered in Pu Trom and Pu Nhav villages in Mondulkiri Province, and Banteay Roka and Banteay Roka Kirisenchey (M) villages in Kampong Speu Province. P. vivax cases were detected (216 cases, 5%) across all enrolled villages. Only two infections were found in forest rangers.\nConclusion: Malaria elimination strategies for forest-exposed populations in Cambodia should focus on vector intervention strategies that offer protection during the day and outside at night, and the use of drug-based strategies to clear subpatent infections, targeting forest goers and dwellers in villages where cases are detected.","manuscriptTitle":"Malaria risk factors amongst forest going populations in Mondulkiri Province and Kampong Speu Province, Cambodia: a large cross-sectional survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-01 08:16:17","doi":"10.21203/rs.3.rs-5291817/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-20T15:02:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-06T08:06:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-04T14:24:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306477664567082171816735703519264371428","date":"2024-10-28T15:54:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49312882971635975323997070944702159477","date":"2024-10-28T14:37:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-28T14:10:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-19T01:02:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-19T01:01:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2024-10-18T22:30:37+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":"7f9ab166-f8f6-439a-b2fb-0516ed2a77f0","owner":[],"postedDate":"November 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:05:02+00:00","versionOfRecord":{"articleIdentity":"rs-5291817","link":"https://doi.org/10.1186/s12936-025-05290-0","journal":{"identity":"malaria-journal","isVorOnly":false,"title":"Malaria Journal"},"publishedOn":"2025-02-22 15:56:54","publishedOnDateReadable":"February 22nd, 2025"},"versionCreatedAt":"2024-11-01 08:16:17","video":"","vorDoi":"10.1186/s12936-025-05290-0","vorDoiUrl":"https://doi.org/10.1186/s12936-025-05290-0","workflowStages":[]},"version":"v1","identity":"rs-5291817","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5291817","identity":"rs-5291817","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}