Malaria Transmission Patterns Research Articles

An observational analysis of the impact of indoor residual spraying in two distinct contexts of Burkina Faso

BackgroundIndoor residual spraying (IRS) is a cornerstone malaria control intervention in Burkina Faso. From 2018 to 2021, non-pyrethroid IRS was implemented annually in two regions of Burkina Faso with distinct malaria transmission patterns, concurrently with annual seasonal malaria chemoprevention (SMC), and a mass insecticide-treated net (ITN) distribution in 2019.MethodsA retrospective quasi-experimental approach was used to evaluate the impact of the 2018, 2020, and 2021 IRS campaigns on routinely reported confirmed malaria case incidence at health facilities. The 2019 campaign was excluded due to lack of data reporting during a health sector strike. Controlled interrupted time series models were fit to detect changes in level and trend in malaria case incidence rates following each IRS campaign when compared to the baseline period 24-months before IRS. IRS districts Solenzo (Sudano-Sahelien climate), and Kampti (tropical climate) were compared with neighbouring control districts and the analyses were stratified by region. Modelled health facility catchment population estimates based on travel time to health facilities and weighted by non-malaria outpatient visits were used as an offset. The study period encompassed July 2016 through June 2022, excluding July 2018 to June 2019.ResultsDistrict-level population and structure coverage achieved by IRS campaigns was greater than 85% in 2018, 2020, and 2021 in Solenzo and Kampti. In Solenzo a significant difference in malaria case incidence rates was detected after the 2018 campaign (IRR = 0.683; 95% CI 0.564–0.827) when compared to the control district. The effect was not detected following the 2020 or 2021 IRS campaigns. In Kampti, estimated malaria incidence rates were between 36 and 38% lower than in the control district following all three IRS campaigns compared to the baseline period.ConclusionsImplementation of IRS in Kampti, a tropical region of Burkina Faso, appeared to have a consistent significant beneficial impact on malaria case rates. An initial positive impact in Solenzo after the first IRS campaign was not sustained in the successive evaluated IRS campaigns. This study points to a differential effect of IRS in different malaria transmission settings and in combination with ITN and SMC implementation.

Unravelling heterogeneous malaria transmission dynamics in the Peruvian Amazon: insights from a cross-sectional survey

BackgroundMalaria remains a global health challenge, particularly in Peru's Loreto region. Despite ongoing efforts, high infection rates and asymptomatic cases perpetuate transmission. The Peruvian Ministry of Health’s “Zero Malaria Plan” targets elimination. This novel study combines microscopic, molecular, and serological techniques to assess transmission intensity, identify epidemiological risk factors, and characterize species-specific patterns across villages. The findings aim to inform targeted interventions and support broader malaria elimination efforts in line with the Zero Malaria Plan initiative.MethodsA cross-sectional malaria survey was conducted in the Zungarococha community, comprising the villages Llanchama (LL), Ninarumi (NI), Puerto Almendra (PA), and Zungarococha (ZG), using microscopic, molecular, and serological techniques to evaluate malaria transmission intensity. Statistical analysis, including multivariate-adjusted analysis, seroprevalence curves, and spatial clustering analysis, were performed to assess malaria prevalence, exposure, and risk factors.ResultsThe survey revealed a high prevalence of asymptomatic infections (6% by microscopy and 18% by PCR), indicating that molecular methods are more sensitive for detecting asymptomatic infections. Seroprevalence varied significantly between villages, reflecting the heterogeneous malaria transmission dynamics. Multivariate analysis identified age, village, and limited bed net use as significant risk factors for malaria infection and species-specific exposure. Seroprevalence curves demonstrated community-specific patterns, with Llanchama and Puerto Almendra showing the highest seroconversion rates for both Plasmodium species.ConclusionsThe study highlights the diverse nature of malaria transmission in the Loreto region, particularly nothing the pronounced heterogeneity as transmission rates decline, especially in residual malaria scenarios. The use of molecular and serological techniques enhances the detection of current infections and past exposure, aiding in the identification of epidemiological risk factors. These findings underscore the importance of using molecular and serological tools to characterize malaria transmission patterns in low-endemic areas, which is crucial for planning and implementing targeted interventions and elimination strategies. This is particularly relevant for initiatives like the Zero Malaria Plan in the Peruvian Amazon.

Descriptive, Hospital-Based, 10-Year Study of Malaria Transmission in Goa, a Southwest Indian State in the Malaria Elimination Phase.

The South Asia International Center of Excellence for Malaria Research, an NIH-funded collaborative program, investigated the epidemiology of malaria in the Indian state of Goa through health facility-based data collected from the Goa Medical College and Hospital (GMC), the state's largest tertiary healthcare facility, between 2012 and 2021. Our study investigated region-specific spatial and temporal patterns of malaria transmission in Goa and the factors driving such patterns. Over the past decade, the number of malaria cases, inpatients, and deaths at the GMC decreased significantly after a peak in 2014-2015. However, the proportion of severe malaria cases increased over the study period. Also, a trend of decreasing average parasitemia and increasing average gametocyte density suggests a shift toward submicroscopic infections and an increase in transmission commitment characteristic of low-transmission regions. Although transmission occurred throughout the year, 75% of the cases occurred between June and December, overlapping with the monsoon (June-October), which featured rainfall above yearly average, minimal diurnal temperature variation, and high relative humidity. Sociodemographic factors also had a significant association with malaria cases, with cases being more frequent in the 15-50-year-old age group, men, construction workers, and people living in urban areas within the GMC catchment region. Our environmental model of malaria transmission projects almost negligible transmission at the beginning of 2025 (annual parasitic index: 0.0095, 95% CI: 0.0075-0.0114) if the current control measures continue undisrupted.

Climate Variability and Malaria Transmission: Unraveling the Complex Relationship

Climate change, an emerging issue, significantly impacts international health, particularly malaria, a critical issue that affects tropical and subtropical areas. Researchers have identified climate variability as a major determinant of malaria transmission and distribution. This review aims to disentangle the interplay between climate variability and malaria transmission, with a focus on temperature, rainfall, humidity, and extreme weather events and their influence on the Anopheles mosquito and Plasmodium parasites' life cycles. Writing this review article involved consulting several scientific databases and compiling information from them. Thus, incorporating data from epidemiology, ecology, climatology, and public health, this paper aimed at integrating knowledge on how climatic factors influence malaria incidence, distribution, and transmission density. This study emphasizes the importance of cross-disciplinary approaches in addressing these issues and highlights the need for synergy in implementing climate change mitigation, improved health care systems, advanced surveillance, and community mobilization to mitigate and manage malaria in the changing climate. Awareness of the factors determining climate variability and their relationship with malaria transmission patterns is important in formulating adequate strategies to cushion the impact of climate change on malaria incidence and secure world health.

Future malaria environmental suitability in Africa is sensitive to hydrology.

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.

Measuring protective efficacy and quantifying the impact of drug resistance: A novel malaria chemoprevention trial design and methodology.

Recently revised WHO guidelines on malaria chemoprevention have opened the door to more tailored implementation. Countries face choices on whether to replace old drugs, target additional age groups, and adapt delivery schedules according to local drug resistance levels and malaria transmission patterns. Regular routine assessment of protective efficacy of chemoprevention is key. Here, we apply a novel modelling approach to aid the design and analysis of chemoprevention trials and generate measures of protection that can be applied across a range of transmission settings. We developed a model of genotype-specific drug protection, which accounts for underlying risk of infection and circulating genotypes. Using a Bayesian framework, we fitted the model to multiple simulated scenarios to explore variations in study design, setting, and participant characteristics. We find that a placebo or control group with no drug protection is valuable but not always feasible. An alternative approach is a single-arm trial with an extended follow-up (>42 days), which allows measurement of the underlying infection risk after drug protection wanes, as long as transmission is relatively constant. We show that the currently recommended 28-day follow-up in a single-arm trial results in low precision of estimated 30-day chemoprevention efficacy and low power in determining genotype differences of 12 days in the duration of protection (power = 1.4%). Extending follow-up to 42 days increased precision and power (71.5%) in settings with constant transmission over this time period. However, in settings of unstable transmission, protective efficacy in a single-arm trial was overestimated by 24.3% if recruitment occurred during increasing transmission and underestimated by 15.8% when recruitment occurred during declining transmission. Protective efficacy was estimated with greater precision in high transmission settings, and power to detect differences by resistance genotype was lower in scenarios where the resistant genotype was either rare or too common. These findings have important implications for the current guidelines on chemoprevention efficacy studies and will be valuable for informing where these studies should be optimally placed. The results underscore the need for a comparator group in seasonal settings and provide evidence that the extension of follow-up in single-arm trials improves the accuracy of measures of protective efficacy in settings with more stable transmission. Extension of follow-up may pose logistical challenges to trial feasibility and associated costs. However, these studies may not need to be repeated multiple times, as the estimates of drug protection against different genotypes can be applied to different settings by adjusting for transmission intensity and frequency of resistance.

Identifying Malaria Hotspots Regions in Ghana Using Bayesian Spatial and Spatiotemporal Models

Abstract Background Malaria remains a significant public health concern in Ghana, with varying risk levels across different geographical areas. Malaria affects millions of people each year and imposes a substantial burden on the health care system and population. Accurate risk estimation and mapping are crucial for effectively allocating resources and implementing targeted interventions to identify regions with disease hotspots. This study aimed to identify regions exhibiting elevated malaria risk so that public health interventions can be implemented, and to identify malaria risk predictors that can be controlled as part of public health interventions for malaria control. Methods The data on laboratory-confirmed malaria cases from 2015 to 2021 were obtained from the Ghana Health Service and Ghana Statistical Service. We studied the spatial and spatiotemporal patterns of the relative risk of malaria using Bayesian spatial and spatiotemporal models. The malaria risk for each region was mapped to visually identify regions with malaria hotspots. Clustering and heterogeneity of disease risks were established using correlated and uncorrelated structures via the conditional autoregressive and Gaussian models, respectively. Parameter estimates from the marginal posterior distribution were estimated within the Integrated Nested Laplace Approximation using the R software. Results The spatial model indicated an increased risk of malaria in the North East, Bono East, Ahafo, Central, Upper West, Brong Ahafo, Ashanti, and Eastern regions. The spatiotemporal model results highlighted an elevated malaria risk in the North East, Upper West, Upper East, Savannah, Bono East, Central, Bono, and Ahafo regions. Both spatial and spatiotemporal models identified the North East, Upper West, Bono East, Central, and Ahafo Regions as hotspots for malaria risk. Substantial variations in risk were evident across regions (H = 104.9, P < 0.001). Although climatic and economic factors influenced malaria infection, statistical significance was not established. Conclusions Malaria risk was clustered and varied among regions in Ghana. There are many regions in Ghana that are hotspots for malaria risk, and climate and economic factors have no significant influence on malaria risk. This study could provide information on malaria transmission patterns in Ghana, and contribute to enhance the effectiveness of malaria control strategies.

Multiple Anopheles species complicate downstream analysis and decision-making in a malaria pre-elimination area in southern Mozambique

BackgroundDifferent anopheline species (even within a species group/complex) can differ in their feeding and resting behaviours, which impact both malaria transmission patterns as well as the efficacy of vector control interventions. While morphological identification of sampled specimens is an important first step towards understanding species diversity and abundance, misidentification can result in the implementation of less effective vector control measures, and consequently smaller reductions in the number of local malaria cases. Focusing on southern Mozambique, a malaria pre-elimination area where malaria remains persistent, the aims of this preliminary study were to use molecular identification (CO1 and ITS2 barcoding) to (1) validate the results from the morphological identification (with a particular focus on Anopheles pharoensis and Anopheles squamosus), and (2) have a closer look at the Anopheles coustani group (which includes Anopheles tenebrosus and Anopheles ziemanni).MethodsFemale anopheline mosquitoes (n = 81) were identified morphologically and subsequently sequenced at the ribosomal DNA internal transcribed spacer region 2 (ITS2) and/or cytochrome oxidase subunit 1 (CO1) loci towards species determination.ResultsOut of the 62 specimens that were identified morphologically to species, 4 (6.5%) were misidentified. Regarding the An. coustani group, morphological identification showed that several members are present in southern Mozambique, including An. coustani sensu lato (s.l.), An. ziemanni and An. tenebrosus. However, based on both ITS2 and CO1 sequences, the exact species remains unknown for the latter two members until voucher sequences are available for comparison.ConclusionThe reason(s) for morphological misidentification of anopheline mosquitoes need to be mitigated. This is usually related to both the capacity (i.e. training) of the microscopist to identify anopheline species, and the information provided in the dichotomous identification key. As the An. coustani complex contributes to (residual) malaria transmission in sub-Saharan Africa, it may play a role in the observed persistent malaria in southern Mozambique. A better baseline characterizing of the local anophelines species diversity and behaviours will allow us to improve entomological surveillance strategies, better understand the impact of vector control on each local vector species, and identify new approaches to target those vector species.

Detection of X-Chromosome Inversions in Anopheles Pharoensis Collected from Egypt and Sudan by PCR Assay

Globally, the WHO estimated 241 million malaria cases with 627000 deaths in Africa in 2020. Studying inversions in the X-chromosomes could detect behavioral changes and efficiency of transmission of Malaria in Anopheles phronesis species. These changes may lead to shifting from becoming a major vector of Malaria after the inability to transmit Malaria. The knowledge of the malaria transmission pattern of Anopheles pharoensis in Sudan needs to be improved. We aimed to detect the presence of any inversions or mutations in Anopheles pharoensis species collected from Egypt and Sudan and to undergo a Polymerase Chain Reaction (PCR) technique to detect mutations or X-chromosome inversions in the Sudanese and Egyptian strains of Anopheles pharoensis also to compare between the X-chromosome of the two species. It is an experimental, analytical study that aimed to detect inversions in the X –chromosomes of Anopheles phronesis collected from Egypt (Faiyoum Governate) and Sudan (Khartoum, Gezira, and Sennar states) of Sudanese Mosquito species. From the gel electrophoresis and PCR assay, inversions were detected by the 100Bp PCR products using primers. Only very few revealed bands from 75 Egyptian strains were detected by bands. The study revealed that Anopheles pharoensis species collected from Egypt have X- chromosome inversions. Inversions were absent in the Sudanese strains. The study also reacted to the fact that Anopheles phronesis could be a sibling species or a species complex, but further studies are needed to prove this. From the results and observations of this investigation, it was recommended to undergo further genetic studies on Anopheles species in Sudan and use of PCR technique in the classification.

Acceptability, Feasibility, Drug Safety, and Effectiveness of a Pilot Mass Drug Administration with a Single Round of Sulfadoxine-Pyrimethamine Plus Primaquine and Indoor Residual Spraying in Communities with Malaria Transmission in Haiti, 2018.

For a malaria elimination strategy, Haiti's National Malaria Control Program piloted a mass drug administration (MDA) with indoor residual spraying (IRS) in 12 high-transmission areas across five communes after implementing community case management and strengthened surveillance. The MDA distributed sulfadoxine-pyrimethamine and single low-dose primaquine to eligible residents during house visits. The IRS campaign applied pirimiphos-methyl insecticide on walls of eligible houses. Pre- and post-campaign cross-sectional surveys were conducted to assess acceptability, feasibility, drug safety, and effectiveness of the combined interventions. Stated acceptability for MDA before the campaign was 99.2%; MDA coverage estimated at 10 weeks post-campaign was 89.6%. Similarly, stated acceptability of IRS at baseline was 99.9%; however, household IRS coverage was 48.9% because of the high number of ineligible houses. Effectiveness measured by Plasmodium falciparum prevalence at baseline and 10 weeks post-campaign were similar: 1.31% versus 1.43%, respectively. Prevalence of serological markers were similar at 10 weeks post-campaign compared with baseline, and increased at 6 months. No severe adverse events associated with the MDA were identified in the pilot; there were severe adverse events in a separate, subsequent campaign. Both MDA and IRS are acceptable and feasible interventions in Haiti. Although a significant impact of a single round of MDA/IRS on malaria transmission was not found using a standard pre- and post-intervention comparison, it is possible there was blunting of the peak transmission. Seasonal malaria transmission patterns, suboptimal IRS coverage, and low baseline parasitemia may have limited the effectiveness or the ability to measure effectiveness.

An archetypes approach to malaria intervention impact mapping: a new framework and example application

BackgroundAs both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.MethodsFirst, dimensionality reduction and clustering techniques were applied to rasterized geospatial environmental and mosquito covariates to find archetypal malaria transmission patterns. Next, mechanistic models were run on a representative site from each archetype to assess intervention impact. Finally, these mechanistic results were reprojected onto each pixel to generate full maps of intervention impact. The example configuration used ERA5 and Malaria Atlas Project covariates, singular value decomposition, k-means clustering, and the Institute for Disease Modeling’s EMOD model to explore a range of three-year malaria interventions primarily focused on vector control and case management.ResultsRainfall, temperature, and mosquito abundance layers were clustered into ten transmission archetypes with distinct properties. Example intervention impact curves and maps highlighted archetype-specific variation in efficacy of vector control interventions. A sensitivity analysis showed that the procedure for selecting representative sites to simulate worked well in all but one archetype.ConclusionThis paper introduces a novel methodology which combines the richness of spatiotemporal mapping with the rigor of mechanistic modeling to create a multi-purpose infrastructure for answering a broad range of important questions in the malaria policy space. It is flexible and adaptable to a range of input covariates, mechanistic models, and mapping strategies and can be adapted to the modelers’ setting of choice.

Naturally acquired antibody response to Plasmodium falciparum and Plasmodium vivax among indigenous Orang Asli communities in Peninsular Malaysia.

Malaria remains a public health problem in many parts of the world. In Malaysia, the significant progress towards the national elimination programme and effective disease notification on malaria has resulted in zero indigenous human malaria cases since 2018. However, the country still needs to determine the extent of malaria exposure and transmission patterns, particularly in high-risk populations. In this study, a serological method was used to measure transmission levels of Plasmodium falciparum and Plasmodium vivax among indigenous Orang Asli communities in Kelantan, Peninsular Malaysia. A community-based cross-sectional survey was conducted in three Orang Asli communities (i.e., Pos Bihai, Pos Gob, and Pos Kuala Betis) in Kelantan from June to July 2019. Antibody responses to malaria were assessed by enzyme-linked immunosorbent assay (ELISA) using two P. falciparum (PfAMA-1 and PfMSP-119) and two P. vivax (PvAMA-1 and PvMSP-119) antigens. Age-adjusted antibody responses were analysed using a reversible catalytic model to calculate seroconversion rates (SCRs). Multiple logistic regression was used to investigate factors associated with malaria exposure. The overall malaria seroprevalence was 38.8% for PfAMA-1, 36.4% for PfMSP-119, 2.2% for PvAMA-1, and 9.3% for PvMSP-119. Between study areas, the proportion of seropositivity for any P. falciparum and P. vivax antigens was significantly highest in Pos Kuala Betis with 34.7% (p < 0.001) and 13.6% (p < 0.001), respectively. For all parasite antigens except for PvAMA-1, the proportion of seropositive individuals significantly increased with age (all p < 0.001). Based on the SCR, there was a higher level of P. falciparum transmission than P. vivax in the study area. Multivariate regression analyses showed that living in Pos Kuala Betis was associated with both P. falciparum (adjusted odds ratio [aOR] 5.6, p < 0.001) and P. vivax (aOR 2.1, p < 0.001) seropositivities. Significant associations were also found between age and seropositivity to P. falciparum and P. vivax antigens. Analysis of community-based serological data helps describe the level of transmission, heterogeneity, and factors associated with malaria exposure among indigenous communities in Peninsular Malaysia. This approach could be an important adjunct tool for malaria monitoring and surveillance in low malaria transmission settings in the country.

Malaria transmission pattern across the Sahelian, humid savanna, highland and forest eco-epidemiological settings in Cameroon

BackgroundMalaria remains a major public health concern in Cameroon. Understanding vector distribution and malaria transmission dynamics is of paramount importance for evaluating the performance of control strategies. This study assesses patterns of malaria transmission in four eco-epidemiological settings in Cameroon.MethodsAdult mosquitoes were collected using Human Landing Catches (HLC) once every 4 months from August 2019 to November 2021 in Kaélé, Tibati, Santchou and Bertoua. Mosquitoes were sorted by genus and Anopheles gambiae sensu lato (s.l.) species complex were identified using PCR. The presence of Plasmodium falciparum circumsporozoite protein (CSP) was measured by ELISA; the entomological inoculation rates (EIR) was estimated in each locality.ResultsA total of 23,536 mosquitoes were collected. Anophelesgambiae and/or Anophelescoluzzii were the main malaria vectors in all sites. Anophelesarabiensis was recorded in low frequency in Kaélé and Tibati. Other species collected included Anopheles funestus, Anophelespharoensis and Anopheles ziemmani. High anopheline biting rates were recorded outdoor in all sites except in Kaélé. Important differences in species biting dynamics were observed between sites. The sporozoite infection rate varied from 0.36 to 4%. The daily EIR was found to vary from 0.07 in Santchou to 0.26 infected bites/man/night (ib/m/n) in Kaélé).ConclusionThe study suggests heterogeneous patterns of malaria transmission in different ecoepidemiological settings across the country. The findings stress the need to improve malaria vector control strategies.

Nigeria at 62: Quagmire of malaria and the urgent need for deliberate and concerted control strategy

BackgroundSub-Saharan Africa (SSA) has disproportionately contributed the majority (95%) of all malaria cases and deaths for more than a decade (2010-2021) and Nigeria contributes the highest in global malaria cases and deaths in the last decade.Main bodyDespite several malaria control initiatives, why is Nigeria still the most endemic malaria country? Published reports have underlined possible reasons for the sustenance of malaria transmission. Malaria transmission pattern in the country is largely and remarkably heterogeneous, hence control measures must take this uniqueness into consideration when designing intervention strategies. Nigeria became 62 years post-independence on the 1st of October, 2022, therefore making positive impacts on all aspects of the country, especially in the health sector becomes imperative more than ever before. To achieve a pre-elimination malaria status, we propose the implementation of focused and calculated research strategies. Such strategies would be consciously geared towards understanding vectorial capacity, susceptibility to approved insecticides, identifying malaria hotspots, and deciphering the genetic structure and architecture of P. falciparum within and between groups and regions. This will provide insight into delineating the inter/intra-regional migration of parasite populations, amongst others.ConclusionWith regard to malaria elimination, Nigeria still has a long way to go. There is a need for dedicated prioritization of research efforts that would provide a basic understanding of the Plasmodium parasite in circulation. Such information will support the implementation of policies that will drive down malaria transmission in Nigeria.

Genomic approaches for monitoring transmission dynamics of malaria: A case for malaria molecular surveillance in Sub-Saharan Africa.

Transmission dynamics is an important indicator for malaria control and elimination. As we move closer to eliminating malaria in Sub-Saharan Africa (sSA), transmission indices with higher resolution (genomic approaches) will complement our current measurements of transmission. Most of the present programmatic knowledge of malaria transmission patterns are derived from assessments of epidemiologic and clinical data, such as case counts, parasitological estimates of parasite prevalence, and Entomological Inoculation Rates (EIR). However, to eliminate malaria from endemic areas, we need to track changes in the parasite population and how they will impact transmission. This is made possible through the evolving field of genomics and genetics, as well as the development of tools for more in-depth studies on the diversity of parasites and the complexity of infections, among other topics. If malaria elimination is to be achieved globally, country-specific elimination activities should be supported by parasite genomic data from regularly collected blood samples for diagnosis, surveillance and possibly from other programmatic interventions. This presents a unique opportunity to track the spread of malaria parasites and shed additional light on intervention efficacy. In this review, various genetic techniques are highlighted along with their significance for an enhanced understanding of transmission patterns in distinct topological settings throughout Sub-Saharan Africa. The importance of these methods and their limitations in malaria surveillance to guide control and elimination strategies, are explored.

Composition of Anopheles Meigen (Diptera: Culicidae) in a peri-urban area of the Eastern Amazon

Malaria vector mosquitoes belong to the genus Anopheles Meigen. The Amazon has been changing due to economic activities such as mining, logging, agriculture, and urbanization, leading to changes in malaria transmission patterns in this region. Therefore, this study aimed to survey Anopheles species in a peri-urban area of Macapá, state of Amapá, Eastern Amazon, Brazil. Human landing catches (HLC) and Shannon light traps were used to collect Anopheles adults at three points. We screened breeding sites in all accessible water reservoirs within a 2 km radius of each collection point to collect immatures and found two species: Anopheles (Nyssorhynchus) albitarsis s.l. Lynch-Arribalzága (35.7%) and Anopheles (Nyssorhynchus) braziliensis (Chagas) (64.3%). A total of 267 winged specimens of Anopheles were collected: A. (N.) braziliensis (62.9%), Anopheles (Anopheles) mattogrossensis Lutz &amp; Neiva (11.6%), Anopheles (Nyssorhynchus) triannulatus s.l. (Neiva &amp; Pinto) (11.6%), A. (N.) albitarsis s.l. Lynch-Arribálzaga (6.7%), Anopheles (Nyssorhynchus) darlingi Root (5.2%), Anopheles (Anopheles) peryassui Dyar &amp; Knab (1.5%), and Anopheles (Nyssorhynchus) nuneztovari Galbadón (0.4%). Considering that Macapá has autochthonous malaria cases, our findings can contribute to developing public health measures in this municipality, therefore helping to protect its habitants.&#x0D;

Entomological indicators of malaria transmission prior to a cluster-randomized controlled trial of a ‘lethal house lure’ intervention in central Côte d’Ivoire

BackgroundA study was conducted prior to implementing a cluster-randomized controlled trial (CRT) of a lethal house lure strategy in central Côte d’Ivoire to provide baseline information on malaria indicators in 40 villages across five health districts.MethodsHuman landing catches (HLC) were performed between November and December 2016, capturing mosquitoes indoors and outdoors between 18.00 and 08.00 h. Mosquitoes were processed for entomological indicators of malaria transmission (human biting, parity, sporozoite, and entomological inoculation rates (EIR)). Species composition and allelic frequencies of kdr-w and ace-1R mutations were also investigated within the Anopheles gambiae complex.ResultsOverall, 15,632 mosquitoes were captured. Anopheles gambiae sensu lato (s.l.) and Anopheles funestus were the two malaria vectors found during the survey period, with predominance for An. gambiae (66.2%) compared to An. funestus (10.3%). The mean biting rate for An. gambiae was almost five times higher than that for An. funestus (19.8 bites per person per night for An. gambiae vs 4.3 bites per person per night for An. funestus) and this was evident indoors and outdoors. Anopheles funestus was more competent to transmit malaria parasites in the study area, despite relatively lower number tested for sporozoite index (4.14% (63/1521) for An. gambiae vs 8.01% (59/736) for An. funestus; χ2 = 12.216; P < 0.0001). There were no significant differences between the proportions infected outdoors and indoors for An. gambiae (4.03 vs 4.13%; χ2 = 0.011; P = 0.9197) and for An. funestus (7.89 vs 8.16%; χ2 = 2.58e−29; P = 1). The majority of both infected vectors with malaria parasites harboured Plasmodium falciparum (93.65% for An. gambiae and 98. 31% for An. funestus). Overall, the EIR range for both species in the different districts appeared to be high (0.35–2.20 infected bites per human per night) with the highest value observed in the district of North-Eastern-Bouaké. There were no significant differences between transmission occurring outdoor and indoor for both species. Of the An. gambiae s.l. analysed, only An. gambiae sensu stricto (14.1%) and Anopheles coluzzii (85.9%) were found. The allelic frequencies of kdr and ace-1R were higher in An. gambiae (0.97 for kdr and 0.19 for ace-1R) than in An. coluzzii (0.86 for kdr and 0.10 for ace-1R) (P < 0.001).ConclusionDespite universal coverage with long-lasting insecticidal nets (LLINs) in the area, there was an abundance of the malaria vectors (An. gambiae and An. funestus) in the study area in central Côte d’Ivoire. Consistent with high insecticide resistance intensity previously detected in these districts, the current study detected high kdr frequency (> 85%), coupled with high malaria transmission pattern, which could guide the use of Eave tubes in the study areas.

Weather integrated malaria prediction system using Bayesian structural time series model for northeast states of India.

Malaria is an endemic disease in India and targeted to eliminate by the year 2030. The present study is aimed at understanding the epidemiological patterns ofmalaria transmission dynamics in Assam and Arunachal Pradesh followed by the development of a malaria prediction model using monthly climate factors. A total of 144,055 cases in Assam during 2011-2018 and 42,970 cases in Arunachal Pradesh were reported during the 2011-2019 period observed, and Plasmodium falciparum (74.5%) was the most predominant parasite in Assam, whereas Plasmodium vivax (66%) in Arunachal Pradesh. Malaria transmission showed a strong seasonal variation where most of the cases were reported during the monsoon period (Assam, 51.9%, and Arunachal Pradesh, 53.6%). Similarly, the malaria incidence was highest in the male population in both states (Asam, 55.75%, and Arunachal Pradesh, 51.43%), and the disease risk is also higher among the > 15years age group (Assam, 61.7%, and Arunachal Pradesh, 67.9%). To predict the malaria incidence, Bayesian structural time series (BSTS) and Seasonal Auto-Regressive Integrated Moving Average with eXogenous factors (SARIMAX) models were implemented. A statistically significant association between malaria cases and climate variables was observed. The most influencing climate factors are found to be maximum and mean temperature with a 6-month lag, and it showed a negative association with malaria incidence. The BSTS model has shown superior performance on the optimal auto-correlated dataset (OAD) which contains auto-correlated malaria cases, cross-correlated climate variables besides malaria cases in both Assam (RMSE, 0.106; MAE, 0.089; and SMAPE, 19.2%) and Arunachal Pradesh (RMSE, 0.128; MAE, 0.122; and SMAPE, 22.6%) than the SARIMAX model. The findings suggest that the predictive performance of the BSTS model is outperformed, and it may be helpful for ongoing intervention strategies by governmental and nongovernmental agencies in the northeast region to combat the disease effectively.

The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: a longitudinal cohort study

The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and the effect of climate change on malaria transmission over 27 years in Hainan, an island province in China. For this longitudinal cohort study, we used a decades-long dataset of malaria incidence reports from Hainan, China, to investigate the pattern of malaria transmission in Hainan relative to temperature and the incidence at increasing altitudes. Climatic data were obtained from the local meteorological stations in Hainan during 1984-2010 and the WorldClim dataset. A temperature-dependent R0 model and negative binomial generalised linear model were used to decipher the relationship between climate factors and malaria incidence in the tropical region. Over the past few decades, the annual peak incidence has appeared earlier in the central highland regions but later in low-altitude regions in Hainan, China. Results from the temperature-dependent model showed that these long-term changes of incidence peak timing are linked to rising temperatures (of about 1·5°C). Further, a 1°C increase corresponds to a change in cases of malaria from -5·6% (95% CI -4·5 to -6·6) to -9·2% (95% CI -7·6 to -10·9) from the northern plain regions to the central highland regions during the rainy season. In the dry season, the change in cases would be 4·6% (95% CI 3·7 to 5·5) to 11·9% (95% CI 9·8 to 14·2) from low-altitude areas to high-altitude areas. Our study empirically supports the idea that increasing temperatures can generate opposing effects on malaria dynamics for lowland and highland regions. This should be further investigated and incorporated into future modelling, disease burden calculations, and malaria control, with attention for central highland regions under climate change. Scientific and Technological Innovation 2030: Major Project of New Generation Artificial Intelligence, National Natural Science Foundation of China, Beijing Natural Science Foundation, National Key Research and Development Program of China, Young Elite Scientist Sponsorship Program by CAST, Research on Key Technologies of Plague Prevention and Control in Inner Mongolia Autonomous Region, and Beijing Advanced Innovation Program for Land Surface Science.

Spatial\u2013temporal clustering of malaria using routinely collected health facility data on the Kenyan Coast

BackgroundThe over-distributed pattern of malaria transmission has led to attempts to define malaria “hotspots” that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast.MethodsData on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff’s spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test.ResultsAcross 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected.ConclusionTaking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.