Malaria Risk Areas Research Articles

Ten-year trend analysis of malaria prevalence in Gindabarat district, West Shawa Zone, Oromia Regional State, Western Ethiopia

BackgroundMalaria is a major public health concern in Ethiopia, where more than half of the population lives in malaria risk areas. While several studies have been conducted in different eco-epidemiological settings in Ethiopia, there is a notable scarcity of data on the prevalence of malaria in the Gindabarat district. Therefore, this study aimed to analyse 10-year trend of malaria prevalence in Gindabarat district, West Shawa Zone of Oromia, Western Ethiopia.MethodsA retrospective laboratory record review was conducted at Gindabarat General Hospital and Gindabarat District Health Office from September 2011 to August 2020. The retrieved data included the date of examination, age, sex and laboratory results of the blood smears, including the Plasmodium species identified. Data were summarized and presented in the form of tables, figures, and frequencies to present the results. The data were analysed using SPSS (version 25.0) and Microsoft Excel.ResultsOver the course of 10 years, a total of 11,478 blood smears were examined in the public health facilities in the district. Of the total blood smears examined, 1372 (11.95%) were microscopically confirmed malaria. Plasmodium falciparum, Plasmodium vivax and mixed infections (P. falciparum and P. vivax) accounted for 70.77%, 20.55% and 8.67% of the cases, respectively. Malaria prevalence was significantly higher among individuals aged ≥ 15 years (12.60%, x2 = 13.6, df = 2, p = 0.001) and males (14.21%, x2 = 59.7, df = 1, p = 0.001). The highest number of malaria cases was recorded from September to November.ConclusionMalaria remains a public health problem in the district. P. falciparum was the most predominant parasite species in the area. Malaria prevalence was significantly higher among individuals aged ≥ 15 years and males. There was a remarkable fluctuation in the number of malaria cases in different months and years. In the study area malaria cases peaked in 2015 and 2017 then decreasing from 2017 to 2019, with sharp increase in 2020. Moreover, this study showed malaria cases were reported in all seasons and months, but the highest was observed from September to November. Strengthening malaria control activities is essential to further reduce the burden of malaria and pave the way for the anticipated elimination.

Physical durability and insecticidal activity of long-lasting insecticidal nets in Cruzeiro do Sul, Brazil

Vector control is one of the principal strategies used for reducing malaria transmission. Long-lasting insecticidal bed nets (LLINs) are a key tool used to protect populations at risk of malaria, since they provide both physical and chemical barriers to prevent human-vector contact. This study aimed to assess the physical durability and insecticidal efficacy of LLINs distributed in Cruzeiro do Sul (CZS), Brazil, after 4 years of use. A total of 3000 LLINs (PermaNet 2.0) were distributed in high malaria risk areas of CZS in 2007. After 4 years of use, 27 ‘rectangular’ LLINs and 28 ‘conical’ LLINs were randomly selected for analysis. The evaluation of physical integrity was based on counting the number of holes and measuring their size and location on the nets. Insecticidal efficacy was evaluated by cone bioassays, and the amount of residual insecticide remaining on the surface of the LLINs was estimated using a colorimetric method. After 4 years of use, physical damage was highly prevalent on the rectangular LLINs, with a total of 473 holes detected across the 27 nets. The upper portion of the side panels sustained the greatest damage in rectangular LLINs. The overall mosquito mortality by cone bioassay was < 80% in 25/27 rectangular LLINs, with panel A (at the end of the rectangular bednet) presenting the highest mortality (54%). The overall mean insecticide concentration was 0.5 µg/sample, with the bednet roof containing the highest average concentration (0.61 µg/sample). On the conical LLINs, 547 holes were detected, with the bottom areas sustaining the greatest damage. The cone bioassay mortality was < 80% in 26/28 of the conical LLINs. The mean insecticide concentration was 0.3 µg/sample. After 4 years of use, the insecticidal efficacy of the LLINs was diminished to below acceptable thresholds.

Geospatial based model for malaria risk prediction in Kilombero valley, South-eastern, Tanzania.

Malaria continues to pose a major public health challenge in tropical regions. Despite significant efforts to control malaria in Tanzania, there are still residual transmission cases. Unfortunately, little is known about where these residual malaria transmission cases occur and how they spread. In Tanzania for example, the transmission is heterogeneously distributed. In order to effectively control and prevent the spread of malaria, it is essential to understand the spatial distribution and transmission patterns of the disease. This study seeks to predict areas that are at high risk of malaria transmission so that intervention measures can be developed to accelerate malaria elimination efforts. This study employs a geospatial based model to predict and map out malaria risk area in Kilombero Valley. Environmental factors related to malaria transmission were considered and assigned valuable weights in the Analytic Hierarchy Process (AHP), an online system using a pairwise comparison technique. The malaria hazard map was generated by a weighted overlay of the altitude, slope, curvature, aspect, rainfall distribution, and distance to streams in Geographic Information Systems (GIS). Finally, the risk map was created by overlaying components of malaria risk including hazards, elements at risk, and vulnerability. The study demonstrates that the majority of the study area falls under moderate risk level (61%), followed by the low risk level (31%), while the high malaria risk area covers a small area, which occupies only 8% of the total area. The findings of this study are crucial for developing spatially targeted interventions against malaria transmission in residual transmission settings. Predicted areas prone to malaria risk provide information that will inform decision-makers and policymakers for proper planning, monitoring, and deployment of interventions.

Spatial analysis and mapping of malaria risk areas using multi-criteria decision making in Ibadan, Oyo state, Nigeria

Malaria is a mosquito-borne infectious disease that affects humans and poses a severe public health problem. Nigeria has the highest number of global cases. Geospatial technology has been widely used to study the risks and factors associated with malaria hazards. The present study is conducted in Ibadan, Oyo State, Nigeria. The objective of this study is to map out areas that are at high risk of the prevalence of malaria by considering a good number of factors as criteria that determine the spread of malaria within Ibadan using open-source and Landsat remote sensing data and further analysis in GIS-based multi-criteria evaluation (MCE). This study considered factors like climate, environmental, socio-economic, and proximity to health centers as criteria for mapping malaria risk. The MCE used a weighted overlay of the factors to produce an element at-risk map, a malaria hazard map, and a vulnerability map. These maps were overlaid to produce the final malaria risk map, which showed that 72% of Ibadan has a risk of malaria prevalence. Identification and delineation of risk areas in Ibadan would help policymakers and decision-makers mitigate the hazards and improve the health status of the state.

Spatio-temporal analysis of malaria incidence and its risk factors in North Namibia

BackgroundMillions of dollars have been spent in fighting malaria in Namibia. However, malaria remains a major public health concern in Namibia, mostly in Kavango West and East, Ohangwena and Zambezi region. The primary goal of this study was to fit a spatio-temporal model that profiles spatial variation in malaria risk areas and investigate possible associations between disease risk and environmental factors at the constituency level in highly risk northern regions of Namibia.MethodsMalaria data, climatic data, and population data were merged and Global spatial autocorrelation statistics (Moran’s I) was used to detect the spatial autocorrelation of malaria cases while malaria occurrence clusters were identified using local Moran statistics. A hierarchical Bayesian CAR model (Besag, York and Mollie’s model “BYM”) known to be the best model for modelling the spatial and temporal effects was then fitted to examine climatic factors that might explain spatial/temporal variation of malaria infection in Namibia.ResultsAverage rainfall received on an annual basis and maximum temperature were found to have a significant spatial and temporal variation on malaria infection. Every mm increase in annual rainfall in a specific constituency in each year increases annual mean malaria cases by 0.6%, same to average maximum temperature. The posterior means of the time main effect (year t) showed a visible slightly increase in global trend from 2018 to 2020.ConclusionThe study discovered that the spatial temporal model with both random and fixed effects best fit the model, which demonstrated a strong spatial and temporal heterogeneity distribution of malaria cases (spatial pattern) with high risk in most of the Kavango West and East outskirt constituencies, posterior relative risk (RR: 1.57 to 1.78).

Spatial analysis of malaria hotspots in Dilla sub-watershed: Western Ethiopia.

This study aimed to examine the spatial variations in malaria hotspots along Dilla sub-watershed in western Ethiopia based on environmental factors for the prevalence; and compare the risk level along with districts and their respective kebele. The purpose was to identify the extent of the community's exposure to the risk of malaria due to their geographical and biophysical situations, and the results contribute to proactive interventions to halt the impacts. The descriptive survey design was used in this study. Ethiopia Central Statistical Agency based meteorological data, digital elevation model, and soil and hydrological data were integrated with other primary data such as the observations of the study area for ground truthing. The spatial analysis tools and software were used for watershed delineation, generating malaria risk map for all variables, reclassification of factors, weighted overlay analysis, and generation of risk maps. The findings of the study reveal that the significant spatial variations in magnitudes of malaria risk have persisted in the watershed due to discrepancy in their geographical and biophysical situations. Accordingly, significant areas in most of the districts in the watershed are characterized by high and moderate in malaria risks. In general, out of the total area of the watershed which accounts 2773 km2, about 54.8% (1522km2) identified as high and moderate malaria risk area. These areas are explicitly identified and mapped along with the districts and kebele in the watershed to make the result suitable for planning proactive interventions and other decision making. The research output may help the government and humanitarian organizations to prioritize the interventions based on identified spatial situations in severity of malaria risks. The study was aimed only for hotspot analysis which may not provide inclusive account for community's vulnerability to malaria. Thus, the findings in this study needs to be integrated with the socio-economic and other relevant data for better malaria management in the area. Therefore, future research should comprehend the analysis of vulnerability to the impacts of malaria through integrating the level of exposure to the risk, for instance identified in this study, with factors of sensitivity and adaptation capacity of the local community.

Analyzing Spatial and Temporal Patterns of Designated Malaria Risk Areas in Nepal from 2018 to 2021.

Background: Nepal is preparing to eliminate malaria by 2026. To evaluate the progress of vector control and prioritize areas for targeted intervention, understanding the recent changing distribution of high and moderate malaria risk areas is vital. Methods: Patterns of designated high and moderate malaria risk wards in Nepal between 2018 and 2021 were analyzed to identify stable and newly generated high- and moderate-risk (HaMR) wards, using the Spatial Temporal Analysis of Moving Polygons (STAMP) method. Results and Conclusions: High-risk and moderate-risk wards decreased by about 55% and the number of districts containing these wards also decreased from 20 to 14. However, several stable and new HaMR wards, mostly in the northwest and the southwest of the country, are apparent, despite intervention efforts. Public health officials should prioritize those wards for malaria surveillance and vector control, and future studies should explore the underlying reasons for persistent risk wards.

Malaria Outbreak Investigation in Nensebo District, West Arsi Zone, Southeast Ethiopia: A case-control study

Background: Malaria-related morbidity and mortality are 94% concentrated in Africa. Ethiopia is one of ten African countries affected by malaria, with 60% of the population living in malaria-risk areas. Recently, seasonal outbreaks have been reported in all regions, including previously malaria-free areas. Nationally, the Nensebo district of the west Arsi zone is classified as having very low transmission. During the 21st WHO week of 2021, Melka Denbi kebele reported an unusually high number of malaria cases to this district. The purpose of this study was to look into the magnitude of the malaria outbreak and the factors that contributed to it. Methods: A descriptive study was followed by an unmatched case-control study on 86 cases and 172 controls who were chosen at random. Malaria cases were those who were confirmed positive by rapid diagnostic test (RDT) and were line-listed at a health facility, while controls were those who lived nearby and were confirmed negative by RDT. At a p-value of 0.05 and a 95% confidence interval, logistic regression was used to identify malaria contracting factors.Results: With a mean age of 22 (12.31SD), the overall attack rate was 20.2/1000. Plasmodium vivax (PV) 105 (52.8%) was the most common. Staying out at night (AOR=3.94; 95%CI: 2.18-7.37) and stagnant water/intermittent river within 1 km of the vicinity were risk factors. Screened houses were protective (AOR=0.49; 95%CI: 0.27-0.89), as was knowledge of malaria transmission (AOR=0.51; 95%CI: 0.28-0.93) and prevention and control methods (AOR=0.50; 95%CI: 0.27-0.93).Conclusion: The illness was caused primarily by PV species known for their relapsing characteristics. Risk factors included stagnant water near homes and sleeping outside at night. Malaria screening centers and increased public awareness reduce the risk of contracting the disease. Our recommendations included regular environmental monitoring, behavioral change communication, ensuring radical cure, and further research with a detailed entomological survey and climate variables.

Malaria transmission in Nepal under climate change: anticipated shifts in extent and season, and comparison with risk definitions for intervention

BackgroundClimate and climate change affect the spatial pattern and seasonality of malaria risk. Season lengths and spatial extents of mapped current and future malaria transmission suitability predictions for Nepal were assessed for a combination of malaria vector and parasites: Anopheles stephensi and Plasmodium falciparum (ASPF) and An. stephensi and Plasmodium vivax (ASPV) and compared with observed estimates of malaria risk in Nepal.MethodsThermal bounds of malaria transmission suitability for baseline (1960–1990) and future climate projections (RCP 4.5 and RCP 8.5 in 2030 and 2050) were extracted from global climate models and mapped for Nepal. Season length and spatial extent of suitability between baseline and future climate scenarios for ASPF and ASPV were compared using the Warren’s I metric. Official 2010 DoHS risk districts (DRDs) and 2021 DoHS risk wards (DRWs), and spatiotemporal incidence trend clusters (ITCs) were overlaid on suitability season length and extent maps to assess agreement, and potential mismatches.ResultsShifts in season length and extent of malaria transmission suitability in Nepal are anticipated under both RCP 4.5 and RCP 8.5 scenarios in 2030 and 2050, compared to baseline climate. The changes are broadly consistent across both future climate scenarios for ASPF and ASPV. There will be emergence of suitability and increasing length of season for both ASPF and ASPV and decreasing length of season for ASPV by 2050. The emergence of suitability will occur in low and no-risk DRDs and outside of high and moderate-risk DRWs, season length increase will occur across all DRD categories, and outside of high and moderate-risk DRWs. The high and moderate risk DRWs of 2021 fall into ITCs with decreasing trend.ConclusionsThe study identified areas of Nepal where malaria transmission suitability will emerge, disappear, increase, and decrease in the future. However, most of these areas are anticipated outside of the government’s current and previously designated high and moderate-risk areas, and thus outside the focus of vector control interventions. Public health officials could use these anticipated changing areas of malaria risk to inform vector control interventions for eliminating malaria from the country, and to prevent malaria resurgence.

Evaluation of a haemozoin-based rapid diagnostic test for diagnosis of imported malaria during the phase of prevention of reestablishment in Sri Lanka

BackgroundSri Lanka, an island nation, has eliminated endemic malaria transmission. Maintaining elimination in the continued presence of vectors requires vigilance in screening people travelling from high malaria-risk areas and a rapid response with focal screening for infections identified in the community. Such screening requires accurate and very rapid assays that enable an immediate response. Both microscopy and rapid diagnostic tests (RDTs) have limitations including sensitivity and speed in screening large numbers, while polymerase chain reaction (PCR) is practical only as laboratory confirmation. This study assessed the utility of ‘Gazelle’, a novel rapid malaria assay based on magneto-optical detection of haemozoin, a by-product of malaria parasite metabolism.MethodsBetween October 2020 and March 2021, two groups of individuals were screened for malaria by four methods, namely, microscopy, Rapid Diagnostic Test (RDT), Gazelle and PCR. Passive case detection was carried out for confirmation of diagnosis amongst individuals suspected of having malaria. Individuals at high-risk of acquiring malaria, namely persons returning from malaria endemic countries, were screened by active case detection.ResultsOf the 440 individuals screened for malaria, nine malaria positives were diagnosed by PCR, microscopy and the HRP2 band of RDT, which included five Plasmodium falciparum infections, two Plasmodium ovale, and one each of Plasmodium vivax and Plasmodium malariae. Gazelle correctly detected the P. vivax, P. ovale and P. malariae infections within the 2 min test time, but did not detect two P. falciparum infections giving a sensitivity of 77.8%. Specificity was 100%.DiscussionThe Gazelle, a portable bench top device proved useful to screen a large number of blood samples for non-falciparum parasites within 5 minutes of sample input. Species differentiation, and improvement in P. falciparum detection, will be important to broaden utility.

A qualitative study of knowledge, attitudes and perceptions towards malaria prevention among people living in rural upper river valleys of Nepal.

Nepal has made significant progress in decreasing the number of malaria cases over the last two decades. Prevention and timely management of malaria are critical for the National Malaria Program in its quest for elimination. The study aimed to explore the knowledge, attitudes and behaviour towards malaria prevention and treatment among people living in rural villages of Khatyad Rural Municipality in Nepal. This qualitative study collected information through virtual in-depth interviews (N = 25) with female and male participants aged between 15 and 72 years. More than half of the participants knew about the causes of malaria, were aware of the complications of untreated malaria and knew that anti-malarial medicines were provided for free at the public health facilities. Participants indicated that their first choice of health care were public health facilities, however limited supply of medications and diagnostics deviated patients to the private sector. While tertiary care costs were not financially viable, participants opted against traditional care for malaria. Factors such as cost of treatment, distance to the health facility and the decision making authority in households influenced health related decisions in the family. Although long-lasting insecticidal nets were distributed and indoor residual spraying was done periodically, several barriers were identified. Increased awareness of malaria prevention and treatment among people living in malaria risk areas is important for the National Malaria Program in its quest for malaria elimination in Nepal.

Assessment of Malaria Risk Using GIS and Multi Criteria: The Case Study of East Gojjam Zone, Ethiopia

Malaria is one of the most severe public health problems worldwide with 300 to 500 million cases and about one million deaths reported to date, 90% of which were reported from Sub Saharan African countries like Ethiopia. The main objective of the study was Assessment of malaria risk areas by using the GIS-based MCA approaches in East Gojjam zone. Weighted overlay technique of multi-criteria analysis was used to develop the malaria risk map. The malaria risk map was produced depending upon the overlay analysis of the malaria hazard map and some factors like land use land cover, population density, health stations. The malaria risk map was classified into four suitability index such as very highly suitable, high suitable, moderately suitable, and low suitable. The result shows that around 21.02% areas is very highly suitable for malaria risk, 24.49% is high suitable, 24.66% is moderately suitable and 29.83 % is low suitable for malaria risk areas. It is suggested that effective identification and mapping of malaria risk areas can be made using geospatial tools, to contribute for the prevention system easily manageable and controlling the disease.

Factors influencing health workers\u2019 compliance with outpatient malaria \u2018test and treat\u2019 guidelines during the plateauing performance phase in Kenya, 2014\u20132016

BackgroundHealth workers’ compliance with outpatient malaria ‘test and treat’ guidelines has improved since 2010 but plateaued from 2014 at suboptimal levels in Kenya. This study examined the factors associated with high but suboptimal compliance levels at facilities with available malaria tests and drugs.MethodsData from four national, cross-sectional health facility surveys undertaken between 2014 and 2016 in Kenya were analysed. Association between 31 factors and compliance with malaria testing (survey range (SR): 65–69%) and no anti-malarial treatment for test negative patients (SR: 90–92%) were examined using multilevel logistic regression models.ResultsA total of 2,752 febrile patients seen by 594 health workers at 486 health facilities were analysed. Higher odds of malaria testing were associated with lake endemic (aOR = 12.12; 95% CI: 5.3–27.6), highland epidemic (aOR = 5.06; 95% CI: 2.7–9.5) and semi-arid seasonal (aOR = 2.07; 95% CI: 1.2–3.6) compared to low risk areas; faith-based (FBO)/ non-governmental organization (NGO)-owned compared to government-owned facilities (aOR = 5.80; 95% CI: 3.2–10.6); health workers’ perception of malaria endemicity as high-risk (aOR = 3.05; 95% CI: 1.8–5.2); supervision with feedback (aOR = 1.84; 95% CI: 1.2–2.9); access to guidelines (aOR = 1.96; 95% CI: 1.1–3.4); older patients compared to infants, higher temperature measurements and main complaints of fever, diarrhoea, headache, vomiting and chills. Lower odds of testing were associated with febrile patients having main complaints of a cough (aOR = 0.65; 95% CI: 0.5–0.9), a rash (aOR = 0.32; 95% CI: 0.2–0.7) or a running nose (aOR = 0.59; 95% CI: 0.4–0.9). Other factors associated with compliance with test negative results included the type of diagnostic test available at the facility, in-service training, health workers’ age, and correct knowledge of the targeted treatment policy.ConclusionsTo optimize outpatient malaria case-management, reduce testing compliance gaps and eliminate overtreatment of test negative patients, there is a need to focus on compliance within low malaria risk areas in addition to ensuring the universal and continuous availability of ‘test and treat’ commodities. Targeting of older and government health workers; dissemination of updated guidelines; and continuing with in-service training and supportive supervision with feedback is essential. Lastly, there is a need to improve health workers’ knowledge about malaria testing criteria considering their perceptions of endemicity.

Vector Bionomics, Potential Vectors, Susceptibility and Bio-efficacy of LLINs Nets on Anopheles Mosquitoes in Nanyin Village Bunmouk Township Sagaing Region in Myanmar

Nanyin village is a malaria endemic area consisting of Bunmouk Township Sagaing Region in Myanmar. Ohnpinkone and Bwedarkone wards were chosen for measuring vector bionomics, potential vectors, susceptibility and bio-efficacy of long lasting insecticidal nets (LLINs) (due to high prevalence of P. falciparum) in both wards from December 2019 to October 2020. A total of 3236 and 3019 Anopheles mosquitoes consist of 12 species were collected from both Ohnpinkone and Bwedarkone wards. Anopheles barbirostris was found highest number (1088 and 820) followed by An. philippinensis (267 and 605) in both areas. Higher number of Anopheles mosquitoes were collected by Cattle bait catching method followed by Indoor Light traps method. The highest was collected in October in Ohnpinkone and September in Bwedarkone. In Ohnpinkone, the highest was collected in April by outdoor and August in indoor light trap and March by outdoor and June by indoor light traps in Bwedarkone. Higher number of main vectors of An. minimus and An. dirus were collected in Ohnpinkone than Bwedarkone and highest number of An. minimus was collected by cattle bait (77) followed by indoor light method (72) in Ohnpinkone. Only 11and 3 An. dirus were collected, of this 9 and 1 number were collected by indoor light traps method from both wards. One An. minimus from Ohnpinkone was found sporozoite positive (0.47%). Main vector An. minimus was collected highest in April in Ohnpinkone and June in Bwedarkone. Susceptibility status of primary and secondary vectors were found susceptible to Pyrethroid insecticides. Bio-efficacy of all tested LLINs nets were found lower efficacy 20% and 63.33% in both wards. Main vector of An. minimus was collected year round in large number in both areas as well as sporozoite positive and An. dirus was available in both areas. Therefore, both areas are highly malaria risk areas and need to proper treatment and control measure using RIS and supply new LLINs nets or retreatment with deltamethrin to old nets according to WHO guideline to ovoid malaria transmission.

Determinants of improvement trends in health workers' compliance with outpatient malaria case-management guidelines at health facilities with available "test and treat" commodities in Kenya.

BackgroundHealth workers’ compliance with outpatient malaria case-management guidelines has been improving in Africa. This study examined the factors associated with the improvements.MethodsData from 11 national, cross-sectional health facility surveys undertaken from 2010–2016 were analysed. Association between 31 determinants and improvement trends in five outpatient compliance outcomes were examined using interactions between each determinant and time in multilevel logistic regression models and reported as an adjusted odds ratio of annual trends (T-aOR).ResultsAmong 9,173 febrile patients seen at 1,208 health facilities and by 1,538 health workers, a higher annual improvement trend in composite “test and treat” performance was associated with malaria endemicity-lake endemic (T-aOR = 1.67 annually; p<0.001) and highland epidemic (T-aOR = 1.35; p<0.001) zones compared to low-risk zone; with facilities stocking rapid diagnostic tests only (T-aOR = 1.49; p<0.001) compared to microscopy only services; with faith-based/non-governmental facilities compared to government-owned (T-aOR = 1.15; p = 0.036); with a daily caseload of >25 febrile patients (T-aOR = 1.46; p = 0.003); and with under-five children compared to older patients (T-aOR = 1.07; p = 0.013). Other factors associated with the improvement trends in the “test and treat” policy components and artemether-lumefantrine administration at the facility included the absence of previous RDT stock-outs, community health workers dispensing drugs, access to malaria case-management and Integrated Management of Childhood Illness (IMCI) guidelines, health workers’ gender, correct health workers’ knowledge about the targeted malaria treatment policy, and patients’ main complaint of fever. The odds of compliance at the baseline were variable for some of the factors.ConclusionsTargeting of low malaria risk areas, low caseload facilities, male and government health workers, continuous availability of RDTs, improving health workers’ knowledge about the policy considering age and fever, and dissemination of guidelines might improve compliance with malaria guidelines. For prompt treatment and administration of the first artemether-lumefantrine dose at the facility, task-shifting duties to community health workers can be considered.

Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique.

Mozambique is a country in Southern Africa with around 30 million inhabitants. Malaria is the leading cause of mortality in the country. According to the WHO, Mozambique has the third highest number of malaria cases in the world, representing approximately 5% of the world total cases. Sussundenga District has the highest incidence in the Manica province and environmental conditions are the major contributor to malaria transmission. There is a lack of malaria risk maps to inform transmission dynamics in Sussundenga village. This study develops a malaria risk map for Sussundenga Village in Mozambique and identifies high risk areas to inform on appropriate malaria control and eradication efforts. One hundred houses were randomly sampled and tested for malaria in Sussundenga Rural Municipality. To construct the map, a spatial conceptual model was used to estimate risk areas using ten environmental and anthropic factors. Data from Worldclim, 30 × 30 Landsat images were used, and layers were produced in a raster data set. Layers between class values were compared by assigning numerical values to the classes within each layer of the map with equal rank. Data set input was classified, using diverse weights depending on their appropriateness. The reclassified data outputs were combined after reclassification. The map indicated a high risk for malaria in the northeast and southeast, that is, the neighborhoods of Nhamazara, Nhamarenza, and Unidade. The central eastern areas, that is, 25 de Junho, 1 and 2, 7 de Abril, and Chicueu presented a moderate risk. In Sussundenga village there was 92% moderate and 8% high risk. High malaria risk areas are most often located in densely populated areas and areas close to water bodies. The relevant findings of this study can inform on effective malaria interventions.

Assessment of Malaria Risk Using GIS and Multi Criteria: The Case Study of East Gojjam Zone, Ethiopia

Malaria is one of the most severe public health problems worldwide with 300 to 500 million cases and about one million deaths reported to date, 90% of which were reported from Sub Saharan African countries like Ethiopia. The main objective of the study was Assessment of malaria risk areas by using the GIS-based MCA approaches in East Gojjam zone. Weighted overlay technique of multi-criteria analysis was used to develop the malaria risk map. The malaria risk map was produced depending upon the overlay analysis of the malaria hazard map and some factors like land use land cover, population density, health stations. The malaria risk map was classified into four suitability index such as very highly suitable, high suitable, moderately suitable, and low suitable. The result shows that around 21.02% areas is very highly suitable for malaria risk, 24.49% is high suitable, 24.66% is moderately suitable and 29.83 % is low suitable for malaria risk areas. Keywords : East Gojjam Zone, Arc GIS, Malaria risk. DOI: 10.7176/CER/12-12-03 Publication date: December 31 st 2020

Projected shifts in the distribution of malaria vectors due to climate change

Climate change is postulated to alter the distribution and abundance of species which serve as vectors for pathogens and is thus expected to affect the transmission of infectious, vector-borne diseases such as malaria. The ability to project and therefore, to mitigate the risk of potential expansion of infectious diseases requires an understanding of how vectors respond to environmental change. Here, we used an extensive dataset on the distribution of the mosquito Anopheles sacharovi, a vector of malaria parasites in Greece, southeast Europe, to build a modeling framework that allowed us to project the potential species range within the next decades. In order to account for model uncertainty, we employed a multi-model approach, combining an ensemble of diverse correlative niche models and a mechanistic model to project the potential expansion of species distribution and to delineate hotspots of potential malaria risk areas. The performance of the models was evaluated using official records on autochthonous malaria incidents. Our projections demonstrated a gradual increase in the potential range of the vector distribution and thus, in the malaria receptive areas over time. Linking the model outputs with human population inhabiting the study region, we found that population at risk increases, relative to the baseline period. The methodological framework proposed and applied here, offers a solid basis for a climate change impact assessment on malaria risk, facilitating informed decision making at national and regional scales.

Trends in health workers\u2019 compliance with outpatient malaria case-management guidelines across malaria epidemiological zones in Kenya, 2010\u20132016

BackgroundHealth workers' compliance with outpatient malaria case-management guidelines has been improving, specifically regarding the universal testing of suspected cases and the use of artemisinin-based combination therapy (ACT) only for positive results (i.e., ‘test and treat’). Whether the improvements in compliance with ‘test and treat’ guidelines are consistent across different malaria endemicity areas has not been examined.MethodsData from 11 national, cross-sectional, outpatient malaria case-management surveys undertaken in Kenya from 2010 to 2016 were analysed. Four primary indicators (i.e., ‘test and treat’) and eight secondary indicators of artemether-lumefantrine (AL) dosing, dispensing, and counselling were measured. Mixed logistic regression models were used to analyse the annual trends in compliance with the indicators across the different malaria endemicity areas (i.e., from highest to lowest risk being lake endemic, coast endemic, highland epidemic, semi-arid seasonal transmission, and low risk).ResultsCompliance with all four ‘test and treat’ indicators significantly increased in the area with the highest malaria risk (i.e., lake endemic) as follows: testing of febrile patients (OR = 1.71 annually; 95% CI = 1.51–1.93), AL treatment for test-positive patients (OR = 1.56; 95% CI = 1.26–1.92), no anti-malarial for test-negative patients (OR = 2.04; 95% CI = 1.65–2.54), and composite ‘test and treat’ compliance (OR = 1.80; 95% CI = 1.61–2.01). In the low risk areas, only compliance with test-negative results significantly increased (OR = 2.27; 95% CI = 1.61–3.19) while testing of febrile patients showed declining trends (OR = 0.89; 95% CI = 0.79–1.01). Administration of the first AL dose at the facility significantly increased in the areas of lake endemic (OR = 2.33; 95% CI = 1.76–3.10), coast endemic (OR = 5.02; 95% CI = 2.77–9.09) and semi-arid seasonal transmission (OR = 1.44; 95% CI = 1.02–2.04). In areas of the lowest risk of transmission and highland epidemic zone, none of the AL dosing, dispensing, and counselling tasks significantly changed over time.ConclusionsThere is variability in health workers' compliance with outpatient malaria case-management guidelines across different malaria-risk areas in Kenya. Major improvements in areas of the highest risk have not been seen in low-risk areas. Interventions to improve practices should be targeted geographically.

Lack of Consistent Malaria Incidence Hotspots in a Highland Kenyan Area During a 10-Year Period of Very Low and Unstable Transmission.

The use of spatial data in malaria elimination strategies is important to understand whether targeted interventions against malaria can be used, particularly in areas with limited resources. We previously documented consistent areas of increased malaria incidence in the epidemic-prone area of Kipsamoite in highland Kenya from 2001 to 2004. In this area and a neighboring subcounty (Kapsisiywa), malaria incidence decreased substantially in 2005, going from peak incidence of 31.7 per 1,000 persons in June 2004 to peak incidence of 7.4 per 1,000 persons in May 2005. Subsequently, the use of indoor residual spraying and artemisinin combination therapy malaria treatment led to a possible interruption of malaria transmission for a 13-month period from 2007 to 2008, after which the incidence returned to very low levels until an epidemic in April-July 2013. In the present study, we used novel kernel density estimation methods to determine whether areas of increased malaria incidence were consistent in six periods of peak incidence from 2003 to 2013, and to assess patterns of incidence in the period before versus. after the period of possible interruption. Areas of highest incidence differed during peak malaria transmission periods over the years 2003-2013, and differed before and after the potential malaria interruption. In this epidemic-prone region with very low malaria transmission, consistent malaria "hotspots" identified in a time of higher transmission are no longer present. Ongoing assessment of spatial malaria epidemiology to identify and target current areas of elevated malaria risk may be important in campaigns to control or eliminate malaria in epidemic-prone areas.