Serological evidence of zoonotic filovirus exposure among bushmeat hunters in Guinea.

Human Ebola virus (EBOV) outbreaks caused by persistent EBOV infection raises questions on the role of zoonotic spillover in filovirus epidemiology. To characterise filovirus zoonotic exposure, we collected cross-sectional serum samples from bushmeat hunters (n = 498) in Macenta Prefecture Guinea, adjacent to the index site of the 2013 EBOV-Makona spillover event. We identified distinct immune signatures (20/498, 4.0%) to multiple EBOV antigens (GP, NP, VP40) using stepwise ELISA and Western blot analysis and, live EBOV neutralisation (5/20; 25%). Using comparative serological data from PCR-confirmed survivors of the 2013-2016 EBOV outbreak, we demonstrated that most signatures (15/20) were not plausibly explained by prior EBOV-Makona exposure. Subsequent data-driven modelling of EBOV immunological outcomes to remote-sensing environmental data also revealed consistent associations with intact closed canopy forest. Together our findings suggest exposure to other closely related filoviruses prior to the 2013-2016 West Africa epidemic and highlight future surveillance priorities.

Landscape drives zoonotic malaria prevalence in non-human primates.

Zoonotic disease dynamics in wildlife hosts are rarely quantified at macroecological scales due to the lack of systematic surveys. Non-human primates (NHPs) host Plasmodium knowlesi, a zoonotic malaria of public health concern and the main barrier to malaria elimination in Southeast Asia. Understanding of regional P. knowlesi infection dynamics in wildlife is limited. Here, we systematically assemble reports of NHP P. knowlesi and investigate geographic determinants of prevalence in reservoir species. Meta-analysis of 6322 NHPs from 148 sites reveals that prevalence is heterogeneous across Southeast Asia, with low overall prevalence and high estimates for Malaysian Borneo. We find that regions exhibiting higher prevalence in NHPs overlap with human infection hotspots. In wildlife and humans, parasite transmission is linked to land conversion and fragmentation. By assembling remote sensing data and fitting statistical models to prevalence at multiple spatial scales, we identify novel relationships between P. knowlesi in NHPs and forest fragmentation. This suggests that higher prevalence may be contingent on habitat complexity, which would begin to explain observed geographic variation in parasite burden. These findings address critical gaps in understanding regional P. knowlesi epidemiology and indicate that prevalence in simian reservoirs may be a key spatial driver of human spillover risk.

Zoonotic diseases are infectious diseases that are transmitted from animals to humans. For example, the malaria-causing parasite Plasmodium knowlesi can be transmitted from monkeys to humans through mosquitos that have previously fed on infected monkeys. In Malaysia, progress towards eliminating malaria is being undermined by the rise of human incidences of 'monkey malaria', which has been declared a public health threat by The World Health Organisation. In humans, cases of monkey malaria are higher in areas of recent deforestation. Changes in habitat may affect how monkeys, insects and humans interact, making it easier for diseases like malaria to pass between them. Deforestation could also change the behaviour of wildlife, which could lead to an increase in infection rates. For example, reduced living space increases contact between monkeys, or it may prevent behaviours that help animals to avoid parasites. Johnson et al. wanted to investigate how the prevalence of malaria in monkeys varies across Southeast Asia to see whether an increase of Plasmodium knowlesi in primates is linked to changes in the landscape. They merged the results of 23 existing studies, including data from 148 sites and 6322 monkeys to see how environmental factors like deforestation influenced the amount of disease in different places. Many previous studies have assumed that disease prevalence is high across all macaques, monkey species that are considered pests, and in all places. But Johnson et al. found that disease rates vary widely across different regions. Overall disease rates in monkeys are lower than expected (only 12%), but in regions with less forest or more 'fragmented' forest areas, malaria rates are higher. Areas with a high disease rate in monkeys tend to further coincide with infection hotspots for humans. This suggests that deforestation may be driving malaria infection in monkeys, which could be part of the reason for increased human infection rates. Johnsons et al.'s study has provided an important step towards better understanding the link between deforestation and the levels of monkey malaria in humans living nearby. Their study provides important insights into how we might find ways of managing the landscape better to reduce health risks from wildlife infection.

Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.

BACKGROUND: In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. RESULTS: We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. CONCLUSIONS: Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

The incidence, and spatial trends of cholera in Sabah over 15 years: Repeated outbreaks in coastal areas.

Vibrio cholerae remains a notable public health challenge across Malaysia. Although the Malaysian state of Sabah is considered a cholera-affected area, gaps remain in understanding the epidemiological trends and spatial distribution of outbreaks. Therefore, to determine longitudinal and spatial trends in cholera cases data were obtained from the Sabah State Health Department for all notified cases of cholera between 2005-2020. A cholera outbreak is defined as one or more confirmed cases in a single locality with the evidence of local transmission. All records were geolocated to village level. Satellite-derived data and generalised linearized models were used to assess potential risk factors, including population density, elevation, and distance to the sea. Spatiotemporal clustering of reported cholera cases and zones of increased cholera risk were evaluated using the tau statistic (τ) at 550m, 5km and 10km distances. Over a 15-year period between 2005-2020, 2865 cholera cases were recorded in Sabah, with a mean incidence rate of 5.6 cases per 100,000 (95% CI: 3.4-7.9). From 2015-2020, 705 symptomatic cases and 727 asymptomatic cases were reported. Symptomatic cases primarily occurred in local Malaysian populations (62.6%, 441/705) and in children and adolescents under 15-years old (49.4%, 348/705). On average, cases were reported in areas with low population density (19.45 persons/km2), low elevations (19.45m) and near coastal areas. Spatiotemporal clustering of cholera cases was identified up to 3.5km, with increased village-level cholera risk within 500m and 5 days of initial case presentation to a health facility (Risk Ratio = 9.7, 95% CI: 7.5-12.4). Cholera incidence has high spatial and temporal heterogeneity within Sabah, with some districts experiencing repeated outbreaks. Cholera cases clustered across space and time, with village-level risk of cholera highest within 5 days and within close proximity to primary case villages, suggesting local transmission.

Disentangling the intersection of inequities with health and malaria exposure: key lessons from rural communities in Northern Borneo.

BACKGROUND: The increasing incidence of Plasmodium knowlesi malaria poses a significant challenge to efforts to eliminate malaria from Malaysia. Macaque reservoirs, outdoors-biting mosquitoes, human activities, and agricultural work are key factors associated with the transmission of this zoonotic pathogen. However, gaps in knowledge regarding reasons that drive malaria persistence in rural Kudat, Sabah, Northern Borneo remain. This study was conducted to address this knowledge gap, to better understand the complexities of these entangled problems, and to initiate discussion regarding new countermeasures to address them. This study aims to highlight rural community members' perspectives regarding inequities to health relating to P. knowlesi malaria exposure. METHODS: From January to October 2022, a study using qualitative methods was conducted in four rural villages in Kudat district of Sabah, Malaysia. A total of nine in-depth interviews were conducted with community and faith leaders, after the completion of twelve focus group discussions with 26 photovoice participants. The interviews were conducted using the Sabah Malay dialect, audio-recorded, transcribed, and translated into English. The research team led the discussion and analysis, which was approved by participants through member checking at the community level. RESULTS: Participants identified disparity in health as a key issue affecting their health and livelihoods. Injustice in the social environment was also identified as a significant challenge, including the importance of listening to the voices of affected communities in disentangling the social and economic phenomena that can impact malaria control. Specific concerns included inadequate access to health-related resources and degradation of the environment. Participants recommended improving access to water and other necessities, increasing the availability of malaria control commodities in healthcare facilities, and developing sustainable programs to reduce socioeconomic disparities. CONCLUSION: Inequities to health emerged as a key concern for malaria control in rural Kudat, Sabah. A locally targeted malaria programme cantered on improving the social and economic disparities associated with health outcomes, could be a potential strategy for malaria prevention in such areas. Community-level perspectives gathered from this study can be used as a foundation for future discussions and dialogues among policymakers and community members for achieving greater transparency, improving social equity, and interoperability in addressing P. knowlesi malaria control.

The public health response to a Plasmodium malariae outbreak in Penampang district, Sabah during a COVID-19 movement control order.

BACKGROUND: Since 2018, no indigenous human malaria cases has been reported in Malaysia. However, during the recent COVID-19 pandemic the World Health Organization is concerned that the pandemic might erode the success of malaria control as there are reports of increase malaria cases in resource limited countries. Little is known how the COVID-19 pandemic has impacted malaria in middle-income countries like Malaysia. Here the public health response to a Plasmodium malariae outbreak occurred in a village in Sabah state, Malaysia, during a COVID-19 movement control order is reported. METHODS: An outbreak was declared following the detection of P. malariae in July 2020 and active case detection for malaria was performed by collecting blood samples from residents residing within 2 km radius of Moyog village. Vector prevalence and the efficacy of residual insecticides were determined. Health awareness programmes were implemented to prevent future outbreaks. A survey was conducted among villagers to understand risk behaviour and beliefs concerning malaria. RESULTS: A total of 5254 blood samples collected from 19 villages. Among them, 19 P. malariae cases were identified, including the index case, which originated from a man who returned from Indonesia. His return from Indonesia and healthcare facilities visit coincided with the movement control order during COVID-19 pandemic when the healthcare facilities stretched its capacity and only serious cases were given priority. Despite the index case being a returnee from a malaria endemic area presenting with mild fever, no malaria test was performed at local healthcare facilities. All cases were symptomatic and uncomplicated except for a pregnant woman with severe malaria. There were no deaths; all patients recovered following treatment with artemether-lumefantrine combination therapy. Anopheles balabacensis and Anopheles barbirostris were detected in ponds, puddles and riverbeds. The survey revealed that fishing and hunting during night, and self-treatment for mild symptoms contributed to the outbreak. Despite the index case being a returnee from a malaria-endemic area presenting with mild fever, no malaria test was performed at local healthcare facilities. CONCLUSION: The outbreak occurred during a COVID-19 movement control order, which strained healthcare facilities, prioritizing only serious cases. Healthcare workers need to be more aware of the risk of malaria from individuals who return from malaria endemic areas. To achieve malaria elimination and prevention of disease reintroduction, new strategies that include multisectoral agencies and active community participation are essential for a more sustainable malaria control programme.

Analytical approaches for antimalarial antibody responses to confirm historical and recent malaria transmission: an example from the Philippines.

Background: Assessing the status of malaria transmission in endemic areas becomes increasingly challenging as countries approach elimination. Serology can provide robust estimates of malaria transmission intensities, and multiplex serological assays allow for simultaneous assessment of markers of recent and historical malaria exposure. Methods: Here, we evaluated different statistical and machine learning methods for analyzing multiplex malaria-specific antibody response data to classify recent and historical exposure to Plasmodium falciparum and Plasmodium vivax. To assess these methods, we utilized samples from a health-facility based survey (n = 9132) in the Philippines, where we quantified antibody responses against 8 P. falciparum and 6 P. vivax-specific antigens from 3 sites with varying transmission intensity. Findings: Measurements of antibody responses and seroprevalence were consistent with the 3 sites' known endemicity status. Among the models tested, a machine learning (ML) approach (Random Forest model) using 4 serological markers (PfGLURP R2, Etramp5.Ag1, GEXP18, and PfMSP119) gave better predictions for P. falciparum recent infection in Palawan (AUC: 0.9591, CI 0.9497-0.9684) than individual antigen seropositivity. Although the ML approach did not improve P. vivax infection predictions, ML classifications confirmed the absence of recent exposure to P. falciparum and P. vivax in both Occidental Mindoro and Bataan. For predicting historical P. falciparum and P. vivax transmission, seroprevalence and seroconversion rates based on cumulative exposure markers AMA1 and MSP119 showed reliable trends in the 3 sites. Interpretation: Our study emphasizes the utility of serological markers in predicting recent and historical exposure in a sub-national elimination setting, and also highlights the potential use of machine learning models using multiplex antibody responses to improve assessment of the malaria transmission status of countries aiming for elimination. This work also provides baseline antibody data for monitoring risk in malaria-endemic areas in the Philippines. Funding: Newton Fund, Philippine Council for Health Research and Development, UK Medical Research Council.

Serological evaluation of risk factors for exposure to malaria in a pre-elimination setting in Malaysian Borneo.

Malaysia has reported no indigenous cases of P. falciparum and P. vivax for over 3 years. When transmission reaches such low levels, it is important to understand the individuals and locations where exposure risks are high, as they may be at greater risk in the case of a resurgence of transmission. Serology is a useful tool in low transmission settings, providing insight into exposure over longer durations than PCR or RDT. We ran blood samples from a 2015 population-based survey in northern Sabah, Malaysian Borneo on a multiplex bead assay. Using supervised machine learning methods, we characterised recent and historic exposure to Plasmodium falciparum and P. vivax and found recent exposure to P. falciparum to be very low, with exposure to both species increasing with age. We performed a risk-factor assessment on environmental, behavioural, demographic and household factors, and identified forest activity and longer travel times to healthcare as common risk-factors for exposure to P. falciparum and P. vivax. In addition, we used remote-sensing derived data and geostatistical models to assess environmental and spatial associations with exposure. We created predictive maps of exposure to recent P. falciparum in the study area and showed 3 clear foci of exposure. This study provides useful insight into the environmental, spatial and demographic risk factors for P. falciparum and P. vivax at a period of low transmission in Malaysian Borneo. The findings would be valuable in the case of resurgence of human malarias in the region.

Exploring barriers to and facilitators of malaria prevention practices: a photovoice study with rural communities at risk to Plasmodium knowlesi malaria in Sabah, Malaysia.

BACKGROUND: The control of Plasmodium knowlesi malaria remains challenging due to the presence of macaque monkeys and predominantly outdoor-biting Anopheles mosquitoes around human settlements. This study aims to explore the barriers and facilitators related to prevention of mosquito bites among rural communities living in Sabah, Malaysia using the participatory visual method, photovoice. METHODS: From January through June 2022, 26 participants were recruited from four villages in Kudat, Sabah, using purposive sampling. Participants were male and female villagers, aged > 18 years old. After photovoice training in the villages, participants documented facilitators of and barriers related to avoiding mosquito bites using their own smartphone cameras, and provided narratives for their photos. Twelve Focus Group Discussions (FGDs) sessions in three rounds were held to share and discuss the photos, and to address challenges to the avoidance of mosquito bites. All discussions were conducted in the Sabah Malay dialect, and were video and audio recorded, transcribed, and analyzed using reflexive thematic analysis. The Ideation Model, a meta-theoretical model of behaviour change, underpinned this study. RESULTS: The most common types of barriers identified by participants included (I) intrapersonal factors such as low perceived threat of malaria, (II) livelihood and lifestyle activities consisting of the local economy and socio-cultural activities, and (III) physical and social environment. The facilitators were categorized into (I) intrapersonal reasons, including having the opportunity to stay indoors, especially women who are housewives, (II) social support by the households, neaighbours and healthcare workers, and (III) support from healthcare services and malaria awareness program. Participants emphasized the importance of stakeholder's support in implementing feasible and affordable approaches to P. knowlesi malaria control. CONCLUSION: Results provided insights regarding the challenges to preventing P. knowlesi malaria in rural Kudat, Sabah. The participation of communities in research was valuable in expanding knowledge of local challenges and highlighting possible ways to overcome barriers. These findings may be used to improve strategies for zoonotic malaria control, which is critical for advancing social change and minimizing health disparities in malaria prevention.

Simian malaria: a narrative review on emergence, epidemiology and threat to global malaria elimination.

Simian malaria from wild non-human primate populations is increasingly recognised as a public health threat and is now the main cause of human malaria in Malaysia and some regions of Brazil. In 2022, Malaysia became the first country not to achieve malaria elimination due to zoonotic simian malaria. We review the global distribution and drivers of simian malaria and identify priorities for diagnosis, treatment, surveillance, and control. Environmental change is driving closer interactions between humans and wildlife, with malaria parasites from non-human primates spilling over into human populations and human malaria parasites spilling back into wild non-human primate populations. These complex transmission cycles require new molecular and epidemiological approaches to track parasite spread. Current methods of malaria control are ineffective, with wildlife reservoirs and primarily outdoor-biting mosquito vectors urgently requiring the development of novel control strategies. Without these, simian malaria has the potential to undermine malaria elimination globally.

No evidence of sustained nonzoonotic Plasmodium knowlesi transmission in Malaysia from modelling malaria case data.

Reported incidence of the zoonotic malaria Plasmodium knowlesi has markedly increased across Southeast Asia and threatens malaria elimination. Nonzoonotic transmission of P. knowlesi has been experimentally demonstrated, but it remains unknown whether nonzoonotic transmission is contributing to increases in P. knowlesi cases. Here, we adapt model-based inference methods to estimate RC, individual case reproductive numbers, for P. knowlesi, P. falciparum and P. vivax human cases in Malaysia from 2012-2020 (n = 32,635). Best fitting models for P. knowlesi showed subcritical transmission (RC < 1) consistent with a large reservoir of unobserved infection sources, indicating P. knowlesi remains a primarily zoonotic infection. In contrast, sustained transmission (RC > 1) was estimated historically for P. falciparum and P. vivax, with declines in RC estimates observed over time consistent with local elimination. Together, this suggests sustained nonzoonotic P. knowlesi transmission is highly unlikely and that new approaches are urgently needed to control spillover risks.

Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance.

Disease control programs are needed to identify the breeding sites of mosquitoes, which transmit malaria and other diseases, in order to target interventions and identify environmental risk factors. The increasing availability of very-high-resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, drone images from two malaria-endemic regions in Burkina Faso and Côte d'Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region-of-interest-based and deep learning methods to identify land cover types associated with vector breeding sites from very-high-resolution natural color imagery. Analysis methods were assessed using cross-validation and achieved maximum Dice coefficients of 0.68 and 0.75 for vegetated and non-vegetated water bodies, respectively. This classifier consistently identified the presence of other land cover types associated with the breeding sites, obtaining Dice coefficients of 0.88 for tillage and crops, 0.87 for buildings and 0.71 for roads. This study establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.

Applications and advances in acoustic monitoring for infectious disease epidemiology.

Emerging infectious diseases continue to pose a significant burden on global public health, and there is a critical need to better understand transmission dynamics arising at the interface of human activity and wildlife habitats. Passive acoustic monitoring (PAM), more typically applied to questions of biodiversity and conservation, provides an opportunity to collect and analyse audio data in relative real time and at low cost. Acoustic methods are increasingly accessible, with the expansion of cloud-based computing, low-cost hardware, and machine learning approaches. Paired with purposeful experimental design, acoustic data can complement existing surveillance methods and provide a novel toolkit to investigate the key biological parameters and ecological interactions that underpin infectious disease epidemiology.

Influence of Landscape Patterns on Exposure to Lassa Fever Virus, Guinea.

Lassa fever virus (LASV) is the causative agent of Lassa fever, a disease endemic in West Africa. Exploring the relationships between environmental factors and LASV transmission across ecologically diverse regions can provide crucial information for the design of appropriate interventions and disease monitoring. We investigated LASV exposure in 2 ecologically diverse regions of Guinea. Our results showed that exposure to LASV was heterogenous between and within sites. LASV IgG seropositivity was 11.9% (95% CI 9.7%-14.5%) in a coastal study site in Basse-Guinée, but it was 59.6% (95% CI 55.5%-63.5%) in a forested study site located in Guinée Forestière. Seropositivity increased with age in the coastal site. We also found significant associations between exposure risk for LASV and landscape fragmentation in coastal and forested regions. Our study highlights the potential link between environmental change and LASV emergence and the urgent need for research on land management practices that reduce disease risks.

The use of drones for mosquito surveillance and control.

In recent years, global health security has been threatened by the geographical expansion of vector-borne infectious diseases such as malaria, dengue, yellow fever, Zika and chikungunya. For a range of these vector-borne diseases, an increase in residual (exophagic) transmission together with ecological heterogeneity in everything from weather to local human migration and housing to mosquito species' behaviours presents many challenges to effective mosquito control. The novel use of drones (or uncrewed aerial vehicles) may play a major role in the success of mosquito surveillance and control programmes in the coming decades since the global landscape of mosquito-borne diseases and disease dynamics fluctuates frequently and there could be serious public health consequences if the issues of insecticide resistance and outdoor transmission are not adequately addressed. For controlling both aquatic and adult stages, for several years now remote sensing data have been used together with predictive modelling for risk, incidence and detection of transmission hot spots and landscape profiles in relation to mosquito-borne pathogens. The field of drone-based remote sensing is under continuous change due to new technology development, operation regulations and innovative applications. In this review we outline the opportunities and challenges for integrating drones into vector surveillance (i.e. identification of breeding sites or mapping micro-environmental composition) and control strategies (i.e. applying larval source management activities or deploying genetically modified agents) across the mosquito life-cycle. We present a five-step systematic environmental mapping strategy that we recommend be undertaken in locations where a drone is expected to be used, outline the key considerations for incorporating drone or other Earth Observation data into vector surveillance and provide two case studies of the advantages of using drones equipped with multispectral cameras. In conclusion, recent developments mean that drones can be effective for accurately conducting surveillance, assessing habitat suitability for larval and/or adult mosquitoes and implementing interventions. In addition, we briefly discuss the need to consider permissions, costs, safety/privacy perceptions and community acceptance for deploying drone activities.

Life table analysis of Anopheles balabacensis, the primary vector of Plasmodium knowlesi in Sabah, Malaysia.

BACKGROUND: Plasmodium knowlesi has become a major public health concern in Sabah, Malaysian Borneo, where it is now the only cause of indigenous malaria. The importance of P. knowlesi has spurred on a series of studies on this parasite, as well as on the biology and ecology of its principal vector, Anopheles balabacensis. However, there remain critical knowledge gaps on the biology of An. balabacensis, such as life history data and life table parameters. To fill these gaps, we conducted a life table study of An. balabacensis in the laboratory. Characterising vector life cycles and survival rates can inform more accurate estimations of the serial interval, the time between two linked cases, which is crucial to understanding and monitoring potentially changing transmission patterns. METHODS: Individuals of An. balabacensis were collected in the field in Ranau district, Sabah to establish a laboratory colony. Induced mating was used, and the life history parameters of the progeny were recorded. The age-stage, two-sex life table approach was used in the analysis. The culture conditions in the laboratory were 9 h light:15 h dark, mean temperature 25.7 °C ± 0.05 and relative humidity 75.8% ± 0.31. RESULTS: The eggs hatched within 2 days, and the larval stage lasted for 10.5 days in total, with duration of instar stages I, II, III and IV of 2.3, 3.7, 2.3, 2.2 days, respectively. The maximum total fecundity was 729 for one particular female, while the maximum female age-specific mean fecundity (mx) was 142 at age 59 days. The gross reproductive rate or number of offspring per individual was about 102. On average, each female laid 1.81 ± 0.19 (range 1-7) batches of eggs, with 63% of the females producing only one batch; only one female laid six batches, while one other laid seven. Each batch comprised 159 ± 17.1 eggs (range 5-224) and the female ratio of offspring was 0.28 ± 0.06. The intrinsic rate of increase, finite rate of increase, net reproductive rate, mean generation time and doubling time were, respectively, 0.12 ± 0.01 day-1, 1.12 ± 0.01 day-1, 46.2 ± 14.97, 33.02 ± 1.85 and 5.97 days. CONCLUSIONS: Both the net reproductive rate and intrinsic rate of increase of An. balabacensis are lower than those of other species in published studies. Our results can be used to improve models of P. knowlesi transmission and to set a baseline for assessing the impacts of environmental change on malaria dynamics. Furthermore, incorporating these population parameters of An. balabacensis into spatial and temporal models on the transmission of P. knowlesi would provide better insight and increase the accuracy of epidemiological forecasting.

Assessing seroprevalence and associated risk factors for multiple infectious diseases in Sabah, Malaysia using serological multiplex bead assays.

Background: Infectious diseases continue to burden populations in Malaysia, especially among rural communities where resources are limited and access to health care is difficult. Current epidemiological trends of several neglected tropical diseases in these populations are at present absent due to the lack of habitual and efficient surveillance. To date, various studies have explored the utility of serological multiplex beads to monitor numerous diseases simultaneously. We therefore applied this platform to assess population level exposure to six infectious diseases in Sabah, Malaysia. Furthermore, we concurrently investigated demographic and spatial risk factors that may be associated with exposure for each disease. Methods: This study was conducted in four districts of Northern Sabah in Malaysian Borneo, using an environmentally stratified, population-based cross-sectional serological survey targeted to determine risk factors for malaria. Samples were collected between September to December 2015, from 919 villages totaling 10,100 persons. IgG responses to twelve antigens of six diseases (lymphatic filariasis- Bm33, Bm14, BmR1, Wb123; strongyloides- NIE; toxoplasmosis-SAG2A; yaws- Rp17 and TmpA; trachoma- Pgp3, Ct694; and giardiasis- VSP3, VSP5) were measured using serological multiplex bead assays. Eight demographic risk factors and twelve environmental covariates were included in this study to better understand transmission in this community. Results: Seroprevalence of LF antigens included Bm33 (10.9%), Bm14+ BmR1 (3.5%), and Wb123 (1.7%). Seroprevalence of Strongyloides antigen NIE was 16.8%, for Toxoplasma antigen SAG2A was 29.9%, and Giardia antigens GVSP3 + GVSP5 was 23.2%. Seroprevalence estimates for yaws Rp17 was 4.91%, for TmpA was 4.81%, and for combined seropositivity to both antigens was 1.2%. Seroprevalence estimates for trachoma Pgp3 + Ct694 were 4.5%. Age was a significant risk factors consistent among all antigens assessed, while other risk factors varied among the different antigens. Spatial heterogeneity of seroprevalence was observed more prominently in lymphatic filariasis and toxoplasmosis. Conclusions: Multiplex bead assays can be used to assess serological responses to numerous pathogens simultaneously to support infectious disease surveillance in rural communities, especially where prevalences estimates are lacking for neglected tropical diseases. Demographic and spatial data collected alongside serosurveys can prove useful in identifying risk factors associated with exposure and geographic distribution of transmission.

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach.

Introduction. Landscape changes disrupt environmental, social and biological systems, altering pathogen spillover and transmission risks. This study aims to quantify the impact of specific land management practices on spillover and transmission rates of zoonotic and vector-borne diseases within Malaysian Borneo. This protocol describes a cohort study with integrated ecological sampling to assess how deforestation and agricultural practices impact pathogen flow from wildlife and vector populations to human infection and detection by health facilities. This will focus on malaria, dengue and emerging arboviruses (Chikungunya and Zika), vector-borne diseases with varying contributions of simian reservoirs within this setting. Methods. A prospective longitudinal observational cohort study will be established in communities residing or working within the vicinity of the Stability of Altered Forest Ecosystems (SAFE) Project, a landscape gradient within Malaysian Borneo encompassing different plantation and forest types. The primary outcome of this study will be transmission intensity of selected zoonotic and vector-borne diseases, as quantified by changes in pathogen-specific antibody levels. Exposure will be measured using paired population-based serological surveys conducted at the beginning and end of the two-year cohort study. Secondary outcomes will include the distribution and infection rates of Aedes and Anopheles mosquito vectors, human risk behaviours and clinical cases reported to health facilities. Longitudinal data on human behaviour, contact with wildlife and GPS tracking of mobility patterns will be collected throughout the study period. This will be integrated with entomological surveillance to monitor densities and pathogen infection rates of Aedes and Anopheles mosquitoes relative to land cover. Within surrounding health clinics, continuous health facility surveillance will be used to monitor reported infections and febrile illnesses. Models will be developed to assess spillover and transmission rates relative to specific land management practices and evaluate abilities of surveillance systems to capture these risks.