Search

Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of ρ = 0.24 ). The addition of humidity and then rainfall improves the comparison ( ρ = 0.62 when humidity added; ρ = 0.70 when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity. [ABSTRACT FROM AUTHOR]

Background: Vector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial. Methods: This study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria's Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029. Results: The estimated mean EIR for the years 2020–2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min–max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min–max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min–max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall. Conclusion: This research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health. [ABSTRACT FROM AUTHOR]

Abstract Background Vector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial. Methods This study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria’s Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029. Results The estimated mean EIR for the years 2020–2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min–max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min–max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min–max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall. Conclusion This research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.

Abstract Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of $$\rho = 0.24$$ ρ = 0.24 ). The addition of humidity and then rainfall improves the comparison ( $$\rho = 0.62$$ ρ = 0.62 when humidity added; $$\rho =0.70$$ ρ = 0.70 when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity.

Abstract Nigeria is the most malaria-endemic country in the world. Vegetation and livestock practices have been linked to malaria transmission but little is known about these in Nigeria. The study aimed to evaluate the influence of vegetation and livestock as predictors of malaria transmission in Nigeria. Secondary data obtained from the Nigerian Demographic and Health Survey’s Geospatial Covariate Datasets Manual were used for the analysis. The survey was carried out successfully in 1389 clusters of thirty (30) households each using a two-stage stratified random sampling design. Hierarchical beta regression models were used to model the associations between malaria incidence, enhanced vegetation index (EVI), and livestock practices. The correlation coefficients for vegetation index and livestock-related variables ranged from − 0.063 to 0.074 and varied significantly with the incidence of malaria in Nigeria (P

Abstract Background Malaria remains a burden globally, with the African region accounting for 94% of the overall disease burden and deaths in 2019. It is the major cause of morbidity and mortality among children in Nigeria. Though different environmental factors have been assessed to influence the distribution and transmission of malaria vectors, there is a shortage of information on how they may influence malaria transmission among under-fives in Nigeria. Methods This study was based on the secondary data analysis of the Nigeria Malaria Indicator Survey 2021. The study sample comprised 10,645 women (aged 15–49) who delivered a child in the 2 years preceding the survey. The study was restricted to under-fives. Logistic regression was used to identify factors associated with the risk of malaria. Results There was a positive association between the risk of malaria and heard/seen malaria messages in the last 6 months (AOR 1.39, 95% CI 1.19–1.62), houses with walls built using rudimentary materials (AOR = 1.38, 95% CI 1.04–1.83), at least 6 children living in the house (AOR 1.22, 95% CI 1.00–1.49), children being 1 or 2 years old was associated with increased odds (AOR 1.89, 95% CI 1.50–2.34 and AOR 1.89, 95% CI 1.52–2.36), children from households with only treated nets (AOR 1.23, 95% CI 1.04–1.46) and those from the North West or South East regions (AOR 1.50, 95% CI 1.10–2.05 and AOR 1.48, 95% CI 1.01–2.16), respectively. All other predictors were not associated with the risk of malaria. Conclusion The factors associated with the risk of malaria in this study included sleeping under treated mosquito nets, the age of the children, residing in the northwest and southeast regions, wall construction material, 6 children and above in the household and hearing/seen malaria messages in the last 6 months. Continuous health education and public health interventions, such as the provision of LLITNs, will reduce the risk of malaria and improve the health and well-being of children under 5 years of age.

ABSTRACTMalaria is a mosquito-borne disease. It is a life-threatening disease primarily found in tropical countries, like Ethiopia. The objective of this study was to assess the spatial distributions of malaria risk using geospatial techniques in Wabi Shebele River Sub-basin, Southeastern Ethiopia. Eleven factors, land use and land cover, topographic wetness index, slope, elevation, soil types, proximity to rivers, rainfall, population density, proximity to main roads, proximity to health services, and surface temperature were considered to produce a malaria risk map. GIS-based multi-criteria evaluation (MCE) technique was applied using weighted overlay analysis and produced three map layer factors—hazard, vulnerability, and element at risk maps. Malaria risk map results show that an area of 1867.8 km2 (33.4%), 2112.7 km2 (37.7%), and 1181.6 km2 (21.1%) were categorized under high, moderate, and low malaria risk levels, respectively. Results reveal that a large portion of the study area is classified under high and moderate spatial malaria risk levels. This indicates that communities living in the study area are prone to the malaria disease. Therefore, there is a critical need to progressively reduce malaria disease distribution through healthcare implementation in prioritized areas. This study is helpful for further study in combating malaria disease distribution and increases the efficiency of expectation efforts by skillfully targeting high and moderate-risk areas.

Nigeria is the most malaria-endemic country in the world. Vegetation and livestock practices have been linked to malaria transmission but little is known about these in Nigeria. The study aimed to evaluate the influence of vegetation and livestock as predictors of malaria transmission in Nigeria. Secondary data obtained from the Nigerian Demographic and Health Survey's Geospatial Covariate Datasets Manual were used for the analysis. The survey was carried out successfully in 1389 clusters of thirty (30) households each using a two-stage stratified random sampling design. Hierarchical beta regression models were used to model the associations between malaria incidence, enhanced vegetation index (EVI), and livestock practices. The correlation coefficients for vegetation index and livestock-related variables ranged from − 0.063 to 0.074 and varied significantly with the incidence of malaria in Nigeria (P < 0.001). The model showed vegetation index, livestock goats, and sheep as positive predictors of malaria transmission. Conversely, livestock chicken and pigs were observed to reduce the risk of malaria. The study recommends the need to take into account local differences in transmission when developing malaria early warning systems that utilize environmental and livestock predictors. [ABSTRACT FROM AUTHOR]

Background Malaria remains a burden globally, with the African region accounting for 94% of the overall disease burden and deaths in 2019. It is the major cause of morbidity and mortality among children in Nigeria. Though different environmental factors have been assessed to influence the distribution and transmission of malaria vectors, there is a shortage of information on how they may influence malaria transmission among under-fives in Nigeria. Methods This study was based on the secondary data analysis of the Nigeria Malaria Indicator Survey 2021. The study sample comprised 10,645 women (aged 15–49) who delivered a child in the 2 years preceding the survey. The study was restricted to under-fives. Logistic regression was used to identify factors associated with the risk of malaria. Results There was a positive association between the risk of malaria and heard/seen malaria messages in the last 6 months (AOR 1.39, 95% CI 1.19–1.62), houses with walls built using rudimentary materials (AOR=1.38, 95% CI 1.04–1.83), at least 6 children living in the house (AOR 1.22, 95% CI 1.00–1.49), children being 1 or 2 years old was associated with increased odds (AOR 1.89, 95% CI 1.50–2.34 and AOR 1.89, 95% CI 1.52–2.36), children from households with only treated nets (AOR 1.23, 95% CI 1.04–1.46) and those from the North West or South East regions (AOR 1.50, 95% CI 1.10–2.05 and AOR 1.48, 95% CI 1.01–2.16), respectively. All other predictors were not associated with the risk of malaria. Conclusion The factors associated with the risk of malaria in this study included sleeping under treated mosquito nets, the age of the children, residing in the northwest and southeast regions, wall construction material, 6 children and above in the household and hearing/seen malaria messages in the last 6 months. Continuous health education and public health interventions, such as the provision of LLITNs, will reduce the risk of malaria and improve the health and well-being of children under 5 years of age. [ABSTRACT FROM AUTHOR]

Africa carries a disproportionately high share of the global malaria burden, accounting for 94% of malaria cases and deaths worldwide in 2019. It is also a politically unstable region and the most vulnerable continent to climate change in recent decades. Knowledge about the modifying impacts of violent conflict on climate-malaria relationships remains limited. Here, we quantify the associations between violent conflict, climate variability, and malaria risk in sub-Saharan Africa using health surveys from 128,326 individuals, historical climate data, and 17,429 recorded violent conflicts from 2006 to 2017. We observe that spatial spillovers of violent conflict (SSVCs) have spatially distant effects on malaria risk. Malaria risk induced by SSVCs within 50 to 100 km from the households gradually increases from 0.1% (not significant, P>0.05) to 6.5% (95% CI: 0 to 13.0%). SSVCs significantly promote malaria risk within the average 20.1 to 26.9 °C range. At the 12-mo mean temperature of 22.5 °C, conflict deaths have the largest impact on malaria risk, with an approximately 5.8% increase (95% CI: 1.0 to 11.0%). Additionally, a pronounced association between SSVCs and malaria risk exists in the regions with 9.2 wet days per month. The results reveal that SSVCs increase population exposure to harsh environments, amplifying the effect of warm temperature and persistent precipitation on malaria transmission. Violent conflict therefore poses a substantial barrier to mosquito control and malaria elimination efforts in sub-Saharan Africa. Our findings support effective targeting of treatment programs and vector control activities in conflict-affected regions with a high malaria risk. [ABSTRACT FROM AUTHOR]

International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for scaling resources and prioritizing aid delivery. However, the reliability of these assessments is often uncertain due to data quality issues. This article introduces a data evaluation framework to assist risk modelers in evaluating data adequacy. We operationalize the concept of "data adequacy" by considering "quality by design" (suitability) and "quality of conformance" (reliability). Based on a use case we developed in collaboration with Médecins Sans Frontières, we assessed data sources popular in spatial malaria risk assessments and related domains, including data from the Malaria Atlas Project, a healthcare facility database, WorldPop population counts, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation estimates, European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecast, and Armed Conflict Location and Event Data Project (ACLED) conflict events data. Our findings indicate that data availability is generally not a bottleneck, and data producers effectively communicate contextual information pertaining to sources, methodology, limitations and uncertainties. However, determining such data's adequacy definitively for supporting humanitarian intervention planning remains challenging due to potential inaccuracies, incompleteness or outdatedness that are difficult to quantify. Nevertheless, the data hold value for awareness raising, advocacy and recognizing trends and patterns valuable for humanitarian contexts. We contribute a domain-agnostic, systematic approach to geodata adequacy evaluation, with the aim of enhancing geospatial risk assessments, facilitating evidence-based decisions. [ABSTRACT FROM AUTHOR]

ABSTRACTGrowing interest in the health burden of malaria in ancient times is complimented by recent DNA confirmation of its presence at several archaeological sites in the Mediterranean. This study presents a model of ancient malaria risk for the region with utility for synthesis and application. The GIS-based model combines malaria risk factors that can be reasonably known for pre-modern times. Calibration, verification, and validation of the model is possible through use of a detailed map of pre-eradication malaria endemicity in Italy, the 1882 Carta della Malaria dell’Italia. The model provides a cross-disciplinary tool by bringing technical GIS capabilities to the evaluation of textual sources having potential malarial connections. The study’s main product is an open access relative malaria risk layer for GIS use and application to historical reconstruction. Example maps using model output and potential use are presented.

BackgroundThe burden of malaria in Uganda remains high, but has become increasingly heterogenous following intensified malaria control. Travel within Uganda is recognized as a risk factor for malaria, but behaviours associated with travel are not well-understood. To address this knowledge gap, malaria-relevant behaviours of cohort participants were assessed during travel and at home in Uganda.MethodsResidents from 80 randomly selected households in Nagongera sub-county, Tororo district were enrolled into a cohort to study malaria in rural Uganda. All participants were given long-lasting insecticidal nets (LLINs) at enrolment and were evaluated every 4 weeks at the study clinic. Participants were asked if they had travelled overnight from their home, and if so, a questionnaire was administered to capture information on travel details and behaviours. Behaviour while travelling was assessed within 4 weeks following travel during the study clinic visit. Behaviour while at home was assessed using a similar questionnaire during two-weekly home visits. Behaviours while travelling vs at home were compared using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual. Analysis of factors associated with LLIN adherence, such as destination and duration of travel, time to bed during travel, gender and age at time of travel, were assessed using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual.ResultsBetween October 2017 and October 2019, 527 participants were enrolled and assessed for travel. Of these, 123 (23.2%) reported taking 211 overnight trips; 149 (70.6%) trips were within Tororo. Participants were less likely to use LLINs when travelling than when at home (41.0% vs. 56.2%, relative risk [RR] 0.73, 95% CI 0.60-0.89, p = 0.002); this difference was noted for women (38.8% vs 59.2%, RR 0.66, 95% CI 0.52-0.83, p = 0.001) but not men (48.3% vs 46.6%, RR 0.96, 95% CI 0.67-1.40, p = 0.85). In an adjusted analysis, factors associated with LLIN use when travelling included destination (travelling to districts not receiving indoor residual spraying [IRS] 65.8% vs Tororo district 32.2%, RR 1.80, 95% CI 1.31-2.46, p  7 nights 60.3% vs one night 24.4%, RR 1.97, 95% CI 1.07-3.64, p = 0.03).ConclusionsTravellers, particularly women, were less likely to use LLINs when travelling than when at home. LLIN adherence was higher among those who travelled to non-IRS districts and for more than 1 week, suggesting that perceived malaria risk influences LLIN use. Strategies are needed to raise awareness of the importance of using LLINs while travelling.

Abstract Background The use of urban lowlands for agriculture contributes to the food security of city- dwellers, but promotes malaria transmission. The objective of the study was to characterize the entomological drivers of malaria transmission in two lowlands (N’Gattakro and Odiennekourani) in the city of Bouaké, Côte d’Ivoire. Methods The human landing catch technique was used to capture mosquitoes in houses located at the edge of two lowlands in Bouaké from February to December 2019. Cultivated surfaces were calculated monthly in both lowlands for each crop type (rice and market gardening) using images acquired by a drone. The different mosquito species were identified morphologically and by PCR analysis for the Anopheles gambiae complex. Anopheles infection by Plasmodium parasites was assessed by quantitative PCR. Mosquito diversity, biting behaviour and rhythmicity, and malaria transmission were determined in each lowland and compared. Results Anopheles gambiae sensu lato (s.l.) was predominant in N’Gattakro and Culex quinquefasciatus in Odiennekourani. Four Anopheles species were identified: An. gambiae s.l. and Anopheles funestus s.l. in both lowlands, Anopheles pharoensis in N’Gattakro, and Anopheles ziemanni in Odiennekourani. Within the An. gambiae complex, three species were caught: An. gambiae sensu stricto (s.s.), Anopheles coluzzii, and Anopheles arabiensis for the first time in Côte d’Ivoire (30.1%, 69.9% and 0% in N’Gattakro, and 45.1%, 52.6% and 2.4% in Odiennekourani, respectively). Anopheles gambiae s.l. species exhibited a significant exophagic behaviour in N’Gattakro (77.1% of outdoor bites versus 52.2% in Odiennekourani). In N’Gattakro, 12.6% of captures occurred before bedtime (09.00 pm) and after waking up (05.00 am), 15.1% in Odiennekourani. The mean human biting rate was higher in N’Gattakro than in Odiennekourani (61.6 versus 15.5 bites per person per night). Overall, Anopheles infection rate was 0.68%, with 0.539 and 0.029 infected bites per person per night in N’Gattakro and Odiennekourani, respectively. Conclusion The risk of malaria in urban agricultural lowland areas is uneven. The role of agricultural developments and irrigation patterns in the production of larval habitat should be explored. The exophagic behaviour of Anopheles vectors raises the question of the residual transmission that needs to be assessed to implement appropriate control strategies.

International policy and humanitarian guidance emphasize the need for precise, subnational malaria risk assessments with cross-regional comparability. Spatially explicit indicator-based assessments can support humanitarian aid organizations in identifying and localizing vulnerable populations for scaling resources and prioritizing aid delivery. However, the reliability of these assessments is often uncertain due to data quality issues. This article introduces a data evaluation framework to assist risk modelers in evaluating data adequacy. We operationalize the concept of “data adequacy” by considering “quality by design” (suitability) and “quality of conformance” (reliability). Based on a use case we developed in collaboration with Médecins Sans Frontières, we assessed data sources popular in spatial malaria risk assessments and related domains, including data from the Malaria Atlas Project, a healthcare facility database, WorldPop population counts, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation estimates, European Centre for Medium-Range Weather Forecasts (ECMWF) precipitation forecast, and Armed Conflict Location and Event Data Project (ACLED) conflict events data. Our findings indicate that data availability is generally not a bottleneck, and data producers effectively communicate contextual information pertaining to sources, methodology, limitations and uncertainties. However, determining such data’s adequacy definitively for supporting humanitarian intervention planning remains challenging due to potential inaccuracies, incompleteness or outdatedness that are difficult to quantify. Nevertheless, the data hold value for awareness raising, advocacy and recognizing trends and patterns valuable for humanitarian contexts. We contribute a domain-agnostic, systematic approach to geodata adequacy evaluation, with the aim of enhancing geospatial risk assessments, facilitating evidence-based decisions.

Background: The use of urban lowlands for agriculture contributes to the food security of city- dwellers, but promotes malaria transmission. The objective of the study was to characterize the entomological drivers of malaria transmission in two lowlands (N'Gattakro and Odiennekourani) in the city of Bouaké, Côte d'Ivoire. Methods: The human landing catch technique was used to capture mosquitoes in houses located at the edge of two lowlands in Bouaké from February to December 2019. Cultivated surfaces were calculated monthly in both lowlands for each crop type (rice and market gardening) using images acquired by a drone. The different mosquito species were identified morphologically and by PCR analysis for the Anopheles gambiae complex. Anopheles infection by Plasmodium parasites was assessed by quantitative PCR. Mosquito diversity, biting behaviour and rhythmicity, and malaria transmission were determined in each lowland and compared. Results: Anopheles gambiae sensu lato (s.l.) was predominant in N'Gattakro and Culex quinquefasciatus in Odiennekourani. Four Anopheles species were identified: An. gambiae s.l. and Anopheles funestus s.l. in both lowlands, Anopheles pharoensis in N'Gattakro, and Anopheles ziemanni in Odiennekourani. Within the An. gambiae complex, three species were caught: An. gambiae sensu stricto (s.s.), Anopheles coluzzii, and Anopheles arabiensis for the first time in Côte d'Ivoire (30.1%, 69.9% and 0% in N'Gattakro, and 45.1%, 52.6% and 2.4% in Odiennekourani, respectively). Anopheles gambiae s.l. species exhibited a significant exophagic behaviour in N'Gattakro (77.1% of outdoor bites versus 52.2% in Odiennekourani). In N'Gattakro, 12.6% of captures occurred before bedtime (09.00 pm) and after waking up (05.00 am), 15.1% in Odiennekourani. The mean human biting rate was higher in N'Gattakro than in Odiennekourani (61.6 versus 15.5 bites per person per night). Overall, Anopheles infection rate was 0.68%, with 0.539 and 0.029 infected bites per person per night in N'Gattakro and Odiennekourani, respectively. Conclusion: The risk of malaria in urban agricultural lowland areas is uneven. The role of agricultural developments and irrigation patterns in the production of larval habitat should be explored. The exophagic behaviour of Anopheles vectors raises the question of the residual transmission that needs to be assessed to implement appropriate control strategies. [ABSTRACT FROM AUTHOR]

Growing interest in the health burden of malaria in ancient times is complimented by recent DNA confirmation of its presence at several archaeological sites in the Mediterranean. This study presents a model of ancient malaria risk for the region with utility for synthesis and application. The GIS-based model combines malaria risk factors that can be reasonably known for pre-modern times. Calibration, verification, and validation of the model is possible through use of a detailed map of pre-eradication malaria endemicity in Italy, the 1882 Carta della Malaria dell’Italia. The model provides a cross-disciplinary tool by bringing technical GIS capabilities to the evaluation of textual sources having potential malarial connections. The study’s main product is an open access relative malaria risk layer for GIS use and application to historical reconstruction. Example maps using model output and potential use are presented. [ABSTRACT FROM AUTHOR]

Background: Travellers frequently visit popular destinations like Brazil, India, Peru, Thailand, and Tanzania, each presenting varying malaria risks. The extent to which travellers enter high-risk malaria-endemic areas in destinations with heterogeneous malaria risk remains unclear. We used geo-location via smartphone application to (i) describe where travellers go within countries with heterogeneous malaria risk (Brazil, India, Peru, Thailand), and (ii) compare mosquito bite prevention behaviours between these destinations and Tanzania, considered entirely high-risk for malaria., Methods: This analysis is a sub-study of the TOURIST2 cohort, which prospectively recruited 1000 travellers (≥ 18 years, travelling ≤ 4 weeks) from Swiss travel clinics (Zurich and Basel) between 09/2017-04/2019. We included 734 travellers to Brazil, India, Peru, Thailand, and Tanzania who provided geo-location data. Daily health and geo-location data were collected using a smartphone application. Malaria risk was categorised using 2022 malaria maps from the Swiss Expert Committee for Travel Medicine., Results: Of the 734 travellers, 525 travelled to Brazil, India, Peru, and Thailand, and 225 to Tanzania. In Brazil, India, Peru, and Thailand, only 2% (n = 13) visited high-risk malaria areas. In Peru, 4% (n = 4) visited a high-risk area; in Brazil, 3% (n = 6); in Thailand, 2% when crossing the border into Myanmar (n = 3); and in India, 0%. Travellers to high-risk areas were more often male (62%), slightly older (median age 42.0), and planned longer trips (median 23.0 days) than other travellers. No participants were diagnosed with malaria. Travellers to Brazil, India, Peru and Thailand used mosquito bite prevention measures less frequently than travellers to Tanzania. Those in Tanzania had higher, but still suboptimal, use of insect spray (65% of travel-days)., Conclusions: Travellers to Brazil, India, Peru, and Thailand rarely visited high-risk malaria areas, and their adherence to mosquito bite prevention measures was generally low. In Tanzania, adherence was higher but still suboptimal., (© The Author(s) 2024. Published by Oxford University Press on behalf of International Society of Travel Medicine.)

Climate change has been linked to increasing rates of malaria infection in Western Kenya. Projections show an increased risk of malaria infection under climate change scenarios, impacting vulnerable populations and placing millions of people at risk. Developing suitable risk management strategies requires understanding the hazard, exposure, vulnerability and response to climate change and malaria risk in the context of other local environmental, socio-economic and socio-cultural factors (including gender) that influence exposure, vulnerability and capacity to cope. This paper draws upon two analytical frameworks, using data gathered from focus group discussions with small-scale farmers in Western Kenya: The Intergovernmental Panel on Climate Change (IPCC) Risk Assessment Framework; and Feminist Political Ecology (FPE) to analyze social constructions underpinning farming responsibilities and decision-making power and how these influence the gendered dimensions of exposure, vulnerability and response to climate change and malaria risk in the community. This paper finds that gender influences the risk of malaria through feminization of agricultural activities in the region, socially constructed gendered responsibilities for care and farm work, which increases exposure and vulnerability to mosquito bites and malaria infection, and socially constructed rights of women to make farming decisions and manage farm income, which influences their capacity to manage risk and cope in the long term. Drawing on these findings, this paper proposes that an intersectional gender lens needs to be incorporated into climate and malaria adaptation policy and programming. It concludes with recommendations for implementing the UNFCCC Enhanced Lima Work Program on Gender at the country levels and the development of gender-responsive climate change and malaria risk management.

Debility due to malaria remains a major constraint to economic growth in many Agrarian economies. In the case of Ethiopia, nearly 70% of the population reside in malaria prone areas with focal and multifocal malaria epidemics, presenting a major challenge to subsistence farmers who rely on family labor supply for agricultural production. Various studies have analysed the economic burden of malaria in developing countries, proposing various interventions to reduce its prevalence. These studies have, however, paid little attention to the role of gender in shaping the impact of malaria infections on agricultural labor supply and productivity. There is evidence of existence of complex and diverse gender norms that shape decision making and gender roles in households in many African countries and may influence the risks of malaria infections within households, and access to services for malaria prevention and control. In this study, we examine the direct and indirect effects of malaria risk on agricultural productivity among smallholder farmers. We deviate from previous research in two main aspects: we examine productivity effects of the disease by sex and age of the infected member of the household and estimate the malaria equations using the fractional response model to overcome the limitations of linear and non-linear econometric estimators for bounded data. We find that malaria significantly reduces crop yields and labor productivity. For instance, a 50% increase in malaria prevalence in a household can reduce the per capita land productivity by US$13.4/year, which is about 7.8% reduction in annual per capita income. The estimated loss in labor productivity is about US$1.38/person-day given a 50% rise in malaria prevalence in a household. The results further reveal differential productivity effects of the disease with respect to gender of the household member infected; the effect is greatest when women and children below 14 years in the household fall sick compared to men. The results highlight the need to strengthen women and children's access to malaria control and prevention services to enhance human health and agricultural productivity. Furthermore, rural development projects may achieve greater health benefits by integrating malaria control interventions with the existing agricultural interventions. [ABSTRACT FROM AUTHOR]

Abstract Background The burden of malaria in Uganda remains high, but has become increasingly heterogenous following intensified malaria control. Travel within Uganda is recognized as a risk factor for malaria, but behaviours associated with travel are not well-understood. To address this knowledge gap, malaria-relevant behaviours of cohort participants were assessed during travel and at home in Uganda. Methods Residents from 80 randomly selected households in Nagongera sub-county, Tororo district were enrolled into a cohort to study malaria in rural Uganda. All participants were given long-lasting insecticidal nets (LLINs) at enrolment and were evaluated every 4 weeks at the study clinic. Participants were asked if they had travelled overnight from their home, and if so, a questionnaire was administered to capture information on travel details and behaviours. Behaviour while travelling was assessed within 4 weeks following travel during the study clinic visit. Behaviour while at home was assessed using a similar questionnaire during two-weekly home visits. Behaviours while travelling vs at home were compared using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual. Analysis of factors associated with LLIN adherence, such as destination and duration of travel, time to bed during travel, gender and age at time of travel, were assessed using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual. Results Between October 2017 and October 2019, 527 participants were enrolled and assessed for travel. Of these, 123 (23.2%) reported taking 211 overnight trips; 149 (70.6%) trips were within Tororo. Participants were less likely to use LLINs when travelling than when at home (41.0% vs. 56.2%, relative risk [RR] 0.73, 95% CI 0.60–0.89, p = 0.002); this difference was noted for women (38.8% vs 59.2%, RR 0.66, 95% CI 0.52–0.83, p = 0.001) but not men (48.3% vs 46.6%, RR 0.96, 95% CI 0.67–1.40, p = 0.85). In an adjusted analysis, factors associated with LLIN use when travelling included destination (travelling to districts not receiving indoor residual spraying [IRS] 65.8% vs Tororo district 32.2%, RR 1.80, 95% CI 1.31–2.46, p 7 nights 60.3% vs one night 24.4%, RR 1.97, 95% CI 1.07–3.64, p = 0.03). Conclusions Travellers, particularly women, were less likely to use LLINs when travelling than when at home. LLIN adherence was higher among those who travelled to non-IRS districts and for more than 1 week, suggesting that perceived malaria risk influences LLIN use. Strategies are needed to raise awareness of the importance of using LLINs while travelling.

Africa carries a disproportionately high share of the global malaria burden, accounting for 94% of malaria cases and deaths worldwide in 2019. It is also a politically unstable region and the most vulnerable continent to climate change in recent decades. Knowledge about the modifying impacts of violent conflict on climate-malaria relationships remains limited. Here, we quantify the associations between violent conflict, climate variability, and malaria risk in sub-Saharan Africa using health surveys from 128,326 individuals, historical climate data, and 17,429 recorded violent conflicts from 2006 to 2017. We observe that spatial spillovers of violent conflict (SSVCs) have spatially distant effects on malaria risk. Malaria risk induced by SSVCs within 50 to 100 km from the households gradually increases from 0.1% (not significant, P>0.05) to 6.5% (95% CI: 0 to 13.0%). SSVCs significantly promote malaria risk within the average 20.1 to 26.9 °C range. At the 12-mo mean temperature of 22.5 °C, conflict deaths have the largest impact on malaria risk, with an approximately 5.8% increase (95% CI: 1.0 to 11.0%). Additionally, a pronounced association between SSVCs and malaria risk exists in the regions with 9.2 wet days per month. The results reveal that SSVCs increase population exposure to harsh environments, amplifying the effect of warm temperature and persistent precipitation on malaria transmission. Violent conflict therefore poses a substantial barrier to mosquito control and malaria elimination efforts in sub-Saharan Africa. Our findings support effective targeting of treatment programs and vector control activities in conflict-affected regions with a high malaria risk., Competing Interests: Competing interests statement:The authors declare no competing interest.

Background It remains unclear whether improving iron status increases malaria risk, and few studies have looked at the effect of host iron status on subsequent malaria infection. We therefore aimed to determine whether a child's iron status influences their subsequent risk of malaria infection in sub-Saharan Africa. Methods We assayed iron and inflammatory biomarkers from community-based cohorts of 1309 Kenyan and 1374 Ugandan children aged 0–7 years and conducted prospective surveillance for episodes of malaria. Poisson regression models were fitted to determine the effect of iron status on the incidence rate ratio (IRR) of malaria using longitudinal data covering a period of 6 months. Models were adjusted for age, sex, parasitemia, inflammation, and study site. Results At baseline, the prevalence of iron deficiency (ID) was 36.9% and 34.6% in Kenyan and Ugandan children, respectively. ID anemia (IDA) affected 23.6% of Kenyan and 17.6% of Ugandan children. Malaria risk was lower in children with ID (IRR, 0.7; 95% confidence interval [CI], 0.6, 0.8; P <.001) and IDA (IRR, 0.7; 95% CI, 0.6, 0.9; P =.006). Low transferrin saturation (<10%) was similarly associated with lower malaria risk (IRR, 0.8; 95% CI, 0.6, 0.9; P =.016). However, variation in hepcidin, soluble transferrin receptors (sTfR), and hemoglobin/anemia was not associated with altered malaria risk. Conclusions ID appears to protect against malaria infection in African children when defined using ferritin and transferrin saturation, but not when defined by hepcidin, sTfR, or hemoglobin. Additional research is required to determine causality. Clinical Trials Registration ISRCTN32849447 [ABSTRACT FROM AUTHOR]

Abstract Background Malaria control in South America has vastly improved in the past decade, leading to a decrease in the malaria burden. Despite the progress, large parts of the continent continue to be at risk of malaria transmission, especially in northern South America. The objectives of this study were to assess the risk of malaria transmission and vector exposure in northern South America using multi-criteria decision analysis. Methods The risk of malaria transmission and vector exposure in northern South America was assessed using multi-criteria decision analysis, in which expert opinions were taken on the key environmental and population risk factors. Results Results from our risk maps indicated areas of moderate-to-high risk along rivers in the Amazon basin, along the coasts of the Guianas, the Pacific coast of Colombia and northern Colombia, in parts of Peru and Bolivia and within the Brazilian Amazon. When validated with occurrence records for malaria, An. darlingi, An. albimanus and An. nuneztovari s.l., t-test results indicated that risk scores at occurrence locations were significantly higher (p

Abstract Background During blood meal, the female mosquito injects saliva able to elicit an immune response in the vertebrate. This immune response has been proven to reflect the intensity of exposure to mosquito bites and risk of infection for vector transmitted pathogens such as malaria. The peptide gSG6-P1 of An. gambiae saliva has been demonstrated to be antigenic and highly specific to Anopheles as a genus. However, the applicability of gSG6-P1 to measure exposure to different Anopheles species endemic in the Americas has yet to be evaluated. The purpose of this pilot study was to test whether human participants living in American countries present antibodies able to recognize the gSG6-P1, and whether these antibodies are useful as a proxy for mosquito bite exposure and malaria risk. Methods We tested human serum samples from Colombia, Chile, and the United States for the presence of IgG antibodies against gSG6-P1 by ELISA. Antibody concentrations were expressed as delta optical density (ΔOD) of each sera tested in duplicates. The difference in the antibody concentrations between groups was tested using the nonparametric Mann Whitney test (independent groups) and the nonparametric Wilcoxon matched-pairs signed rank test (dependent groups). All differences were considered significant with a P

Temperature is a key environmental driver of Anopheles mosquito population dynamics; understanding its central role is important for these malaria vectors. Mosquito population responses to temperature fluctuations, though important across the life history, are poorly understood at a population level. We used stage-structured, temperature-dependent delay-differential equations to conduct a detailed exploration of the impacts of diurnal and annual temperature fluctuations on mosquito population dynamics. The model allows exploration of temperature-driven temporal changes in adult age structure, giving insights into the population’s capacity to vector malaria parasites. Because of temperature-dependent shifts in age structure, the abundance of potentially infectious mosquitoes varies temporally, and does not necessarily mirror the dynamics of the total adult population. In addition to conducting the first comprehensive theoretical exploration of fluctuating temperatures on mosquito population dynamics, we analysed observed temperatures at four locations in Africa covering a range of environmental conditions. We found both temperature and precipitation are needed to explain the observed malaria season in these locations, enhancing our understanding of the drivers of malaria seasonality and how temporal disease risk may shift in response to temperature changes. This approach, tracking both mosquito abundance and age structure, may be a powerful tool for understanding current and future malaria risk.

For modelling the spatial distribution of malaria incidence, accurate and detailed information on population size and distribution are of significant importance. Different, global, spatial, standard datasets of population distribution have been developed and are widely used. However, most of them are not up-to-date and the low spatial resolution of the input census data has limitations for contemporary, national- scale analyses. The AfriPop project, launched in July 2009, was initiated with the aim of producing detailed, contemporary and easily updatable population distribution datasets for the whole of Africa. High-resolution satellite sensors can help to further improve this dataset through the generation of high-resolution settlement layers at greater spatial details. In the present study, the settlement extents included in the MALAREO land use classification were used to generate an enhanced and updated version of the AfriPop dataset for the study area covering southern Mozambique, eastern Swaziland and the malarious part of KwaZulu-Natal in South Africa. Results show that it is possible to easily produce a detailed and updated population distribution dataset applying the AfriPop modelling approach with the use of high-resolution settlement layers and population growth rates. The 2007 and 2011 population datasets are freely available as a product of the MALAREO project and can be downloaded from the project website.

Malaria affects about half of the world’s population, with the vast majority of cases occuring in Africa. National malaria control programmes aim to reduce the burden of malaria and its negative, socioeconomic effects by using various control strategies (e.g. vector control, environmental management and case tracking). Vector control is the most effective transmission prevention strategy, while environmental factors are the key parameters affecting transmission. Geographic information systems (GIS), earth observation (EO) and spatial modelling are increasingly being recognised as valuable tools for effective management and malaria vector control. Issues previously inhibiting the use of EO in epidemiology and malaria control such as poor satellite sensor performance, high costs and long turnaround times, have since been resolved through modern technology. The core goal of this study was to develop and implement the capabilities of EO data for national malaria control programmes in South Africa, Swaziland and Mozambique. High- and very high resolution (HR and VHR) land cover and wetland maps were generated for the identification of potential vector habitats and human activities, as well as geoinformation on distance to wetlands for malaria risk modelling, population density maps, habitat foci maps and VHR household maps. These products were further used for modelling malaria incidence and the analysis of environmental factors that favour vector breeding. Geoproducts were also transferred to the staff of national malaria control programmes in seven African countries to demonstrate how EO data and GIS can support vector control strategy planning and monitoring. The transferred EO products support better epidemiological understanding of environmental factors related to malaria transmission, and allow for spatio-temporal targeting of malaria control interventions, thereby improving the cost-effectiveness of interventions.

Background: There is little data on the risk factors for malaria infection in large cities in central Africa and in all age groups. There may be different associations with the risk factors for areas with different malaria transmission intensities such as the effect of fever or age. This study aimed at identifying risk factors associated with Plasmodium infection and anaemia among children 6-59 months and individuals aged older than 5 years in Kinshasa, a large city with heterogeneity in malaria prevalence. Methods: This study analysed data from 3342 children aged 6-59 months from 25 non-rural health zones (HZs) and for 816 individuals aged older than 5 years from two HZs in Kinshasa (non-rural), collected during a cross sectional malaria survey in 2011. Logistic regression with random effects was used to investigate predictors for malaria and anaemia. Differences in risk factors in areas with a prevalence of less than 10 and 10 % or greater were investigated. Results: There was evidence of a different age-pattern in the two transmission settings. For children under 5 years, the highest prevalence of malaria was observed in the 48-59 months group in both transmission settings, but it increased more gently for the lower transmission HZs (p = 0.009). In a separate analysis in children over 5 years in two selected HZs, the peak prevalence was in 5-9 years old in the higher transmission setting and in 15-19 years old in the lower transmission setting. Reported fever was associated with malaria in both transmission strata, with no evidence of a difference in these associations (p = 0.71); however in children older than 5 years there was a significant interaction with a stronger association in the low transmission HZ. Insecticide-treated net (ITN) use was associated with a lower risk of malaria infection in children 6-59 months in the high transmission HZs. Similar estimates were found in children over 5 years and the lower transmission HZ but the associations there were not significant. There was no evidence of a difference in these associations by strata. The risk of anaemia decreased with increasing age in all strata, whereas it increased with malaria infection and reported fever. ITN use did not show evidence of protection against anaemia. Low socio-economic status was associated with malaria in high transmission setting in children 6-59 months and anaemia in low transmission setting. Conclusions: This study shows that in areas of low transmission in Kinshasa, the peak prevalence occurs in older age groups however ITN use was highest in children under 5 years. Targeted distribution of ITN to all age groups should be continued. For most risk factors, there was no evidence of an interaction with transmission intensity however the associations with age and with fever in the last 2 weeks did vary significantly. [ABSTRACT FROM AUTHOR]

Background: Malaria control in South America has vastly improved in the past decade, leading to a decrease in the malaria burden. Despite the progress, large parts of the continent continue to be at risk of malaria transmission, especially in northern South America. The objectives of this study were to assess the risk of malaria transmission and vector exposure in northern South America using multi-criteria decision analysis.Methods: The risk of malaria transmission and vector exposure in northern South America was assessed using multi-criteria decision analysis, in which expert opinions were taken on the key environmental and population risk factors.Results: Results from our risk maps indicated areas of moderate-to-high risk along rivers in the Amazon basin, along the coasts of the Guianas, the Pacific coast of Colombia and northern Colombia, in parts of Peru and Bolivia and within the Brazilian Amazon. When validated with occurrence records for malaria, An. darlingi, An. albimanus and An. nuneztovari s.l., t-test results indicated that risk scores at occurrence locations were significantly higher (p < 0.0001) than a control group of geographically random points.Conclusion: In this study, we produced risk maps based on expert opinion on the spatial representation of risk of potential vector exposure and malaria transmission. The findings provide information to the public health decision maker/policy makers to give additional attention to the spatial planning of effective vector control measures. Therefore, as the region tackles the challenge of malaria elimination, prioritizing areas for interventions by using spatially accurate, high-resolution (1 km or less) risk maps may guide targeted control and help reduce the disease burden in the region. [ABSTRACT FROM AUTHOR]