Anopheles sacharovi in Italy: first record of the historical malaria vector after over 50 years.

BACKGROUND: Anopheles sacharovi, a member of the Anopheles maculipennis complex, was a historical malaria vector in Italy, no longer found since the last report at the end of 1960s. In September 2022, within the Surveillance Project for the residual anophelism, a single specimen of An. maculipennis sensu lato collected in Lecce municipality (Apulia region) was molecularly identified as An. sacharovi. This record led to implement a targeted entomological survey in September 2023. METHODS: Investigation was conducted in the areas around the first discovery, focusing on animal farms, riding stables and potential breeding sites. Adult and immature mosquitoes were collected, using active search or traps, in several natural and rural sites. Mosquitoes belonging to An. maculipennis complex were identified morphologically and molecularly by a home-made routine quantitative polymerase chain reaction (qPCR) assay, developed specifically for the rapid identification of An. labranchiae, and, when necessary, by amplification and sequencing of the ITS-2 molecular marker. RESULTS: Out of the 11 sites investigated, 6 were positive for Anopheles presence. All 20 An. maculipennis s.l. (7 adults, 10 larvae and 3 pupae) collected in the areas were identified as An. sacharovi by ITS-2 sequencing. CONCLUSIONS: The discovery of An. sacharovi, considered to have disappeared from Italy for over 50 years, has a strong health relevance and impact, highlighting an increase in the receptivity of the southern areas. As imported malaria cases in European countries are reported every year, the risk of Plasmodium introduction by gametocyte carriers among travellers from endemic countries should be taken into greater consideration. Our findings allow rethinking and building new models for the prediction and expansion of introduced malaria. Furthermore, to prevent the risk of reintroduction of the disease, the need to strengthen the surveillance of residual anophelism throughout the South should be considered.

Identifying and characterizing high-risk populations in pilot malaria elimination districts in Madagascar: a mixed-methods study.

BACKGROUND: In Madagascar, the districts of Antsirabe II, Faratsiho and Antsiranana I have relatively low malaria incidence rates and have been selected by the National Malaria Control Programme for pilot elimination strategies. The districts have residual transmission despite increasing coverage and quality of malaria services. This study sought to identify priority subpopulations at highest risk for malaria and collect information on intervention preferences and methods that will inform subnational tailoring of malaria service delivery. METHODS: This mixed methods study employed (i) a quantitative malaria risk factor assessment in Antsirabe II and Faratsiho comprising a test-negative frequency matched case-control study and a qualitative risk factor assessment in Antsiranana I; and (ii) a qualitative formative assessment in all three districts. For the case-control study, a mixed effects logistic regression was used with age, sex and district included as fixed effects and health facility included as a random effect. The qualitative risk factor assessment used semi-structured interview guides and key informant interviews. For the qualitative formative assessment in the three districts, a summary report was generated following semi-structured interviews and focus group discussions with high-risk populations (HRPs) and stakeholders. RESULTS: In Antsirabe II and Faratsiho districts, rice agriculture workers, outdoor/manual workers, particularly miners, and those with jobs that required travel or overnight stays, especially itinerant vendors, had higher odds of malaria infection compared to other (non-rice) agricultural workers. In Antsiranana I, respondents identified non-rice farmers, mobile vendors, and students as HRPs. Risk factors among these groups included overnight stays and travel patterns combined with a lack of malaria prevention tools. HRPs reported treatment cost and distance to the health facility as barriers to care and expressed interest in presumptive treatment and involvement of gatekeepers or people who have influence over intervention access or participation. CONCLUSIONS: The study results illustrate the value of in-depth assessments of risk behaviours, access to services and prevention tools, surveillance and prevention strategies, and the involvement of gatekeepers in shaping subnational tailoring to reach previously unreached populations and address residual transmission in elimination settings.

Design of a novel intelligent computing framework for predictive solutions of malaria propagation model.

The paper presents an innovative computational framework for predictive solutions for simulating the spread of malaria. The structure incorporates sophisticated computing methods to improve the reliability of predicting malaria outbreaks. The study strives to provide a strong and effective tool for forecasting the propagation of malaria via the use of an AI-based recurrent neural network (RNN). The model is classified into two groups, consisting of humans and mosquitoes. To develop the model, the traditional Ross-Macdonald model is expanded upon, allowing for a more comprehensive analysis of the intricate dynamics at play. To gain a deeper understanding of the extended Ross model, we employ RNN, treating it as an initial value problem involving a system of first-order ordinary differential equations, each representing one of the seven profiles. This method enables us to obtain valuable insights and elucidate the complexities inherent in the propagation of malaria. Mosquitoes and humans constitute the two cohorts encompassed within the exposition of the mathematical dynamical model. Human dynamics are comprised of individuals who are susceptible, exposed, infectious, and in recovery. The mosquito population, on the other hand, is divided into three categories: susceptible, exposed, and infected. For RNN, we used the input of 0 to 300 days with an interval length of 3 days. The evaluation of the precision and accuracy of the methodology is conducted by superimposing the estimated solution onto the numerical solution. In addition, the outcomes obtained from the RNN are examined, including regression analysis, assessment of error autocorrelation, examination of time series response plots, mean square error, error histogram, and absolute error. A reduced mean square error signifies that the model's estimates are more accurate. The result is consistent with acquiring an approximate absolute error close to zero, revealing the efficacy of the suggested strategy. This research presents a novel approach to solving the malaria propagation model using recurrent neural networks. Additionally, it examines the behavior of various profiles under varying initial conditions of the malaria propagation model, which consists of a system of ordinary differential equations.

Study protocol: improving response to malaria in the Amazon through identification of inter-community networks and human mobility in border regions of Ecuador, Peru and Brazil.

INTRODUCTION: Understanding human mobility's role in malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission. METHODS: We measure community connectivity across the study area using a respondent driven sampling design among key informants who are at least 18 years of age. 45 initial communities will be selected: 10 in Brazil, 10 in Ecuador and 25 in Peru. Participants will be recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses will be ranked and the 2-3 most connected communities will then be selected and surveyed. This process will be repeated for a third round of data collection. Community network matrices will be linked with each country's malaria surveillance system to test the effects of mobility on disease risk. ETHICS AND DISSEMINATION: This study protocol has been approved by the institutional review boards of Duke University (USA), Universidad San Francisco de Quito (Ecuador), Universidad Peruana Cayetano Heredia (Peru) and Universidade Federal Minas Gerais (Brazil). Results will be disseminated in communities by the end of the study.

Effect of spatiotemporal variables on abundance, biting activity and parity of Nyssorhynchus darlingi (Diptera: Culicidae) in peri-Iquitos, Peru.

BACKGROUND: In malaria endemic regions of the Peruvian Amazon, rainfall together with river level and breeding site availability drive fluctuating vector mosquito abundance and human malaria cases, leading to temporal heterogeneity. The main variables influencing spatial transmission include location of communities, mosquito behaviour, land use/land cover, and human ecology/behaviour. The main objective was to evaluate seasonal and microgeographic biting behaviour of the malaria vector Nyssorhynchus (or Anopheles) darlingi in Amazonian Peru and to investigate effects of seasonality on malaria transmission. METHODS: We captured mosquitoes from 18:00 to 06:00 h using Human Landing Catch in two riverine (Lupuna, Santa Emilia) and two highway (El Triunfo, Nuevo Horizonte) communities indoors and outdoors from 8 houses per community, during the dry and rainy seasons from February 2016 to January 2017. We then estimated parity rate, daily survival and age of a portion of each collection of Ny. darlingi. All collected specimens of Ny. darlingi were tested for the presence of Plasmodium vivax or Plasmodium falciparum sporozoites using real-time PCR targeting the small subunit of the 18S rRNA. RESULTS: Abundance of Ny. darlingi varied across village, season, and biting behaviour (indoor vs outdoor), and was highly significant between rainy and dry seasons (p < 0.0001). Biting patterns differed, although not significantly, and persisted regardless of season, with peaks in highway communities at ~ 20:00 h in contrast to biting throughout the night (i.e., 18:00-06:00) in riverine communities. Of 3721 Ny. darlingi tested for Plasmodium, 23 (0.62%) were infected. We detected Plasmodium-infected Ny. darlingi in both community types and most (20/23) were captured outdoors during the rainy season; 17/23 before midnight. Seventeen Ny. darlingi were infected with P. vivax, and 6 with P. falciparum. No infected Ny. darlingi were captured during the dry season. Significantly higher rates of parity were detected in Ny. darlingi during the rainy season (average 64.69%) versus the dry season (average 36.91%) and by community, Lupuna, a riverine village, had the highest proportion of parous to nulliparous females during the rainy season. CONCLUSIONS: These data add a seasonal dimension to malaria transmission in peri-Iquitos, providing more evidence that, at least locally, the greatest risk of malaria transmission is outdoors during the rainy season mainly before midnight, irrespective of whether the community was located adjacent to the highway or along the river.

Malaria elimination: situation analysis of cases in India, the state of Madhya Pradesh in central India, and district Mandla of Madhya Pradesh.

India contributed approximately 66% of the malaria cases in the WHO South-East Asia region in 2022. In India, approximately 44% of cases have been reported to be disproportionately contributed by approximately 27 districts. A comparative analysis of reported malaria cases between January 2017 and December 2022 was performed in Mandla district, which is the site of a model malaria elimination demonstration project (MEDP) in Madhya Pradesh (MP), India. Compared to 2017, the decrease in malaria cases in Mandla from 2018 to 2022 was higher than MP and the rest of the country. The reduction of cases was significant in 2018, 2019, and 2021 (p < 0.01) (Mandla vs. MP) and was highly significant during 2018-2022 (p < 0.001) (Mandla vs. India). Robust surveillance and real-time data-based decisions accompanied by appropriate management, operational controls, and independent reviews, all designed for resource optimisation, were the reasons for eliminating indigenous malaria in Mandla district. The increase in infection rates during the months immediately following rains suggests that surveillance, vector control, and case management efforts should be specifically intensified for eliminating imported and indigenous cases in the near-elimination districts to work towards achieving the national elimination goal of 2030.

COVID-19 and malaria co-infection: a systematic review of clinical outcomes in endemic areas.

Background: COVID-19 and malaria cause significant morbidity and mortality globally. Co-infection of these diseases can worsen their impact on public health. This review aims to synthesize literature on the clinical outcomes of COVID-19 and malaria co-infection to develop effective prevention and treatment strategies. Methods: A comprehensive literature search was conducted using MeSH terms and keywords from the start of the COVID-19 pandemic to January 2023. The review included original articles on COVID-19 and malaria co-infection, evaluating their methodological quality and certainty of evidence. It was registered in PROSPERO (CRD42023393562). Results: Out of 1,596 screened articles, 19 met the inclusion criteria. These studies involved 2,810 patients, 618 of whom had COVID-19 and malaria co-infection. Plasmodium falciparum and vivax were identified as causative organisms in six studies. Hospital admission ranged from three to 18 days. Nine studies associated co-infection with severe disease, ICU admission, assisted ventilation, and related complications. One study reported 6% ICU admission, and mortality rates of 3%, 9.4%, and 40.4% were observed in four studies. Estimated crude mortality rates were 10.71 and 5.87 per 1,000 person-days for patients with and without concurrent malaria, respectively. Common co-morbidities included Diabetes mellitus, hypertension, cardiovascular diseases, and respiratory disorders. Conclusion: Most patients with COVID-19 and malaria co-infection experienced short-term hospitalization and mild to moderate disease severity. However, at presentation, co-morbidities and severe malaria were significantly associated with higher mortality or worse clinical outcomes. These findings emphasize the importance of early detection, prompt treatment, and close monitoring of patients with COVID-19 and malaria co-infection.

Molecular tools are crucial for malaria elimination.

The eradication of Plasmodium parasites, responsible for malaria, is a daunting global public health task. It requires a comprehensive approach that addresses symptomatic, asymptomatic, and submicroscopic cases. Overcoming this challenge relies on harnessing the power of molecular diagnostic tools, as traditional methods like microscopy and rapid diagnostic tests fall short in detecting low parasitaemia, contributing to the persistence of malaria transmission. By precisely identifying patients of all types and effectively characterizing malaria parasites, molecular tools may emerge as indispensable allies in the pursuit of malaria elimination. Furthermore, molecular tools can also provide valuable insights into parasite diversity, drug resistance patterns, and transmission dynamics, aiding in the implementation of targeted interventions and surveillance strategies. In this review, we explore the significance of molecular tools in the pursuit of malaria elimination, shedding light on their key contributions and potential impact on public health.

Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017.

BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogeneity in sociodemographic and environmental risk factors over time and across diverse geographical and climatological regions make outbreak prediction challenging. Data-driven approaches accounting for spatiotemporal variability could offer potential for location-specific early warning tools for malaria. METHODS: In this case study, we developed and internally validated a data fusion approach to predict malaria incidence in Pakistan, India, and Bangladesh using geo-referenced environmental factors. For 2000-17, district-level malaria incidence rates for each country were obtained from the US Agency for International Development's Demographic and Health Survey datasets. Environmental factors included average annual temperature, rainfall, and normalised difference vegetation index, obtained from the Advancing Research on Nutrition and Agriculture (known as AReNA) project conducted by the International Food Policy Research Institute in 2020. Data on night-time light intensity was derived from two satellites of the National Oceanic and Atmospheric Administration Defense Meteorological Satellite Program-Operational Linescan System: Nighttime Lights Time Series Version 4, and VIIRS Nighttime Day/Night Band Composites version 1. A multi-dimensional spatiotemporal long short-term memory (M-LSTM) model was developed using data from 2000-16 and internally validated for the year 2017. The M-LSTM model consisted of four hidden layers, each with 100 LSTM units; a fully connected layer was used, followed by linear regression, to predict the malaria incidence rate for 2017 using spatiotemporal partitioning. Model performance was measured using accuracy and root mean squared error. Country-specific models were produced for Bangladesh, India, and Pakistan. Bivariate geospatial heatmaps were produced for a qualitative comparison of univariate environmental factors with malaria rates. FINDINGS: Malaria incidence was predicted with 80·6% accuracy in districts across Pakistan, 76·7% in districts across India, and 99·1% in districts across Bangladesh. The root mean squared error was 7 × 10-4 for Pakistan, 4·86 × 10-6 for India, and 1·32 × 10-5 for Bangladesh. Bivariate maps showed an inverse relationship between night-time lights and malaria rates; whereas high malaria rates were found in areas with high temperature, rainfall, and vegetation. INTERPRETATION: Malaria outbreaks could be forecasted using remotely measured environmental factors. Modelling techniques that enable simultaneously forecasting ahead in time as well as across large geographical areas might potentially empower regional decision makers to manage outbreaks early. FUNDING: NIHR Oxford Biomedical Research Centre Programme and The Higher Education Commission of Pakistan.

Spatiotemporal distribution and bionomics of Anopheles stephensi in different eco-epidemiological settings in Ethiopia.

BACKGROUND: Malaria is a major public health concern in Ethiopia, and its incidence could worsen with the spread of the invasive mosquito species Anopheles stephensi in the country. This study aimed to provide updates on the distribution of An. stephensi and likely household exposure in Ethiopia. METHODS: Entomological surveillance was performed in 26 urban settings in Ethiopia from 2021 to 2023. A kilometer-by-kilometer quadrant was established per town, and approximately 20 structures per quadrant were surveyed every 3 months. Additional extensive sampling was conducted in 50 randomly selected structures in four urban centers in 2022 and 2023 to assess households' exposure to An. stephensi. Prokopack aspirators and CDC light traps were used to collect adult mosquitoes, and standard dippers were used to collect immature stages. The collected mosquitoes were identified to species level by morphological keys and molecular methods. PCR assays were used to assess Plasmodium infection and mosquito blood meal source. RESULTS: Catches of adult An. stephensi were generally low (mean: 0.15 per trap), with eight positive sites among the 26 surveyed. This mosquito species was reported for the first time in Assosa, western Ethiopia. Anopheles stephensi was the predominant species in four of the eight positive sites, accounting for 75-100% relative abundance of the adult Anopheles catches. Household-level exposure, defined as the percentage of households with a peridomestic presence of An. stephensi, ranged from 18% in Metehara to 30% in Danan. Anopheles arabiensis was the predominant species in 20 of the 26 sites, accounting for 42.9-100% of the Anopheles catches. Bovine blood index, ovine blood index and human blood index values were 69.2%, 32.3% and 24.6%, respectively, for An. stephensi, and 65.4%, 46.7% and 35.8%, respectively, for An. arabiensis. None of the 197 An. stephensi mosquitoes assayed tested positive for Plasmodium sporozoite, while of the 1434 An. arabiensis mosquitoes assayed, 62 were positive for Plasmodium (10 for P. falciparum and 52 for P. vivax). CONCLUSIONS: This study shows that the geographical range of An. stephensi has expanded to western Ethiopia. Strongly zoophagic behavior coupled with low adult catches might explain the absence of Plasmodium infection. The level of household exposure to An. stephensi in this study varied across positive sites. Further research is needed to better understand the bionomics and contribution of An. stephensi to malaria transmission.

Insights and challenges of insecticide resistance modelling in malaria vectors: a review.

BACKGROUND: Malaria is one of the most devastating tropical diseases, resulting in loss of lives each year, especially in children under the age of 5 years. Malaria burden, related deaths and stall in the progress against malaria transmission is evident, particularly in countries that have moderate or high malaria transmission. Hence, mitigating malaria spread requires information on the distribution of vectors and the drivers of insecticide resistance (IR). However, owing to the impracticality in establishing the critical need for real-world information at every location, modelling provides an informed best guess for such information. Therefore, this review examines the various methodologies used to model spatial, temporal and spatio-temporal patterns of IR within populations of malaria vectors, incorporating pest-biology parameters, adopted ecological principles, and the associated modelling challenges. METHODS: The review focused on the period ending March 2023 without imposing restrictions on the initial year of publication, and included articles sourced from PubMed, Web of Science, and Scopus. It was also limited to publications that deal with modelling of IR distribution across spatial and temporal dimensions and excluded articles solely focusing on insecticide susceptibility tests or articles not published in English. After rigorous selection, 33 articles met the review's elibility criteria and were subjected to full-text screening. RESULTS: Results show the popularity of Bayesian geostatistical approaches, and logistic and static models, with limited adoption of dynamic modelling approaches for spatial and temporal IR modelling. Furthermore, our review identifies the availability of surveillance data and scarcity of comprehensive information on the potential drivers of IR as major impediments to developing holistic models of IR evolution. CONCLUSIONS: The review notes that incorporating pest-biology parameters, and ecological principles into IR models, in tandem with fundamental ecological concepts, potentially offers crucial insights into the evolution of IR. The results extend our knowledge of IR models that provide potentially accurate results, which can be translated into policy recommendations to combat the challenge of IR in malaria control.

Low long-lasting insecticidal net use in malaria elimination areas in Southern Ethiopia: results from community based cross-sectional study.

BACKGROUND: Despite remarkable progress in malaria burden reduction, malaria continues to be a major public health problem globally. Ethiopia has been distributing long-lasting insecticidal nets (LLINs) for free and nationwide distribution was completed in 2016. However, evidence suggests that the utilization of LLINs varies from setting to setting and from time to time due to different factors, and up-to-date evidence is required for LLIN related decision-making. Hence, this study was designed to assess LLIN utilization and its determinants in the Southern Nations, Nationalities, and People's Region (SNNPR) of Ethiopia. METHODS: A community-based cross-sectional study was conducted in Southern Ethiopia in 2019. Using multi-stage sampling, a total of 2466 households were included. The region was stratified based on the annual malaria index as high, moderate, low, and free strata. Cluster sampling was then applied to select households from high, moderate, and low strata. Data on LLIN ownership, utilization and different determinant factors were collected using household questionnaire. SurveyCTO was used to collect data and data was managed using Stata 15. Descriptive statistics and multilevel mixed-effects logistic regression were performed to identify the determinants of utilization of LLINs. Effect measures were reported using adjusted odds ratio (AOR) with 95% CI. RESULTS: From a total of 2466 households, 48.7% of households had at least one LLIN. LLIN adequacy based on family size was 23% while it was15.7% based on universal access and 29.2% based on sleeping space. From 1202 households that possessed LLIN(s), 66.0% of households reported that they slept under LLIN the night preceding the survey. However, when the total population in all surveyed households were considered, only 22.9% of household members slept under LLIN the night preceding the survey. Malaria endemicity, educational status, wealth status, and knowledge about malaria were associated with LLINs utilization. In addition, reasons for non-use included perceived absence of malaria, side effects of LLIN, conditions of LLINs, inconvenient space and low awareness. CONCLUSION: Low LLIN coverage and low utilization were noted. A low level of utilization was associated with malaria endemicity, wealth status and level of awareness. Distribution of LLIN and continuous follow-up with community awareness creation activities are vital to improve coverage and utilization of LLINs, and to ensure the country's malaria elimination goal.

Association of ABO, Rh-D and Kell blood groups with transfusion transmitted infections among blood donors from the Asir Region, Saudi Arabia: A retrospective observational study.

OBJECTIVES: To evaluate the association between transfusion-transmitted infections (TTIs) and ABO, Rh-D, and Kell blood systems among blood donors. METHODS: This was a retrospective study of 10,095 donors who visited the Blood Bank at Asir Hospital, Abha, Saudi Arabia. Data including demographic information, ABO, Rh-D, and Kell blood groups, and serological and molecular test results of TTIs (the TTIs were obtained from each donor's records). Chi-squared and Fisher's exact tests were employed to establish possible associations between blood groups and TTIs. RESULTS: The prevalence rate of TTIs among donors was 6.3%, with HBcAb (70%) being the most prevalent biomarker among positive donors. Donors with the O blood group were at a higher risk of contracting TTIs. Significant associations were observed between HIV and blood group A (χ2=6.30, p=0.01), HBsAg and group AB (χ2=17.3193, p=0.00003), malaria and group A (χ2=5.0567, p=0.02), and HBV-DNA and group AB (χ2=12.3163, p=0.0004). Also, Kell blood group was significantly associated with HIV (χ2=14.5, p=0.0001), HBcAb (χ2=78.51, p<0.0001), and syphilis (χ2=25.225, p<0.00001). CONCLUSION: ABO and Kell blood groups are associated with TTI markers. These findings highlight the need for improved strategies and approaches in screening and managing blood donations to minimize the risk of TTIs.

Spatial spillovers of violent conflict amplify the impacts of climate variability on malaria risk in sub-Saharan Africa.

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.

From erosion to epidemics: Understanding the overlapping vulnerability of hydrogeomorphic hotspots, malaria affliction, and poverty in Nigeria.

Hydrogeomorphic changes, encompassing erosion, waterlogging, and siltation, disproportionately threaten impoverished rural communities. Yet, they are often marginalized in discussions of disasters. This oversight is especially concerning as vulnerable households with limited healthcare access are most susceptible to related diseases and displacement. However, our current understanding of how these risks intersect remains limited. We explore the complex relationships between hydrogeomorphic hazards, malaria incidence, and poverty in Nigeria. Through spatial analyses we expand traditional boundaries, incorporating factors such as healthcare access, migration patterns, dam locations, demographics, and wealth disparities into a unified framework. Our findings reveal a stark reality: most residents in hydrogeomorphic hotspots live in poverty (earnings per person ≤$1.25/day), face elevated malaria risks (80 % in malaria hotspots), reside near dams (59 %), and struggle with limited healthcare access. Moreover, exposure to hydrogeomorphic hotspots could double by 2080, affecting an estimated 5.8 million Nigerians. This forecast underscores the urgent need for increased support and targeted interventions to protect those living in poverty within these hazardous regions. In shedding light on these dynamics, we expose and emphasise the pressing urgency of the risks borne by the most vulnerable populations residing in these regions-communities often characterised by limited wealth and resilience.

The effect of explicit convection on simulated malaria transmission across Africa.

Malaria transmission across sub-Saharan Africa is sensitive to rainfall and temperature. Whilst different malaria modelling techniques and climate simulations have been used to predict malaria transmission risk, most of these studies use coarse-resolution climate models. In these models convection, atmospheric vertical motion driven by instability gradients and responsible for heavy rainfall, is parameterised. Over the past decade enhanced computational capabilities have enabled the simulation of high-resolution continental-scale climates with an explicit representation of convection. In this study we use two malaria models, the Liverpool Malaria Model (LMM) and Vector-Borne Disease Community Model of the International Centre for Theoretical Physics (VECTRI), to investigate the effect of explicitly representing convection on simulated malaria transmission. The concluded impact of explicitly representing convection on simulated malaria transmission depends on the chosen malaria model and local climatic conditions. For instance, in the East African highlands, cooler temperatures when explicitly representing convection decreases LMM-predicted malaria transmission risk by approximately 55%, but has a negligible effect in VECTRI simulations. Even though explicitly representing convection improves rainfall characteristics, concluding that explicit convection improves simulated malaria transmission depends on the chosen metric and malaria model. For example, whilst we conclude improvements of 45% and 23% in root mean squared differences of the annual-mean reproduction number and entomological inoculation rate for VECTRI and the LMM respectively, bias-correcting mean climate conditions minimises these improvements. The projected impact of anthropogenic climate change on malaria incidence is also sensitive to the chosen malaria model and representation of convection. The LMM is relatively insensitive to future changes in precipitation intensity, whilst VECTRI predicts increased risk across the Sahel due to enhanced rainfall. We postulate that VECTRI's enhanced sensitivity to precipitation changes compared to the LMM is due to the inclusion of surface hydrology. Future research should continue assessing the effect of high-resolution climate modelling in impact-based forecasting.

Changes in the endemic-epidemic pattern of malaria in Colombia, 1978-2021.

BACKGROUND: Malaria is a major global public health issue with varying epidemiologies across countries. In Colombia, it is a priority endemic-epidemic event included in the national public health policy. However, evidence demonstrating nationwide variations in the disease behavior is limited. This study aimed to analyze changes in the levels and distribution of endemic-epidemic malaria transmission in the eco-epidemiological regions of Colombia from 1978 to 1999 and 2000 to 2021. METHODS: We conducted a comprehensive time-series study using official secondary data on malaria-associated morbidity and mortality in Colombia from 1978 to 2021. Temporal-spatial and population variables were analyzed, and the absolute and relative frequency measures of general and regional morbidity and mortality were estimated. RESULTS: We observed an 18% reduction in malaria endemic cases between the two study periods. The frequency and severity of the epidemic transmission of malaria varied less and were comparable across both periods. A shift was observed in the frequency of parasitic infections, with a tendency to match and increase infections by Plasmodium falciparum. The risk of malaria transmission varied significantly among the eco-epidemiological regions during both study periods. This study demonstrated a sustained decrease of 78% in malarial mortality. CONCLUSIONS: Although the endemic components of malaria decreased slightly between the two study periods, the epidemic pattern persisted. There were significant variations in the risk of transmission across the different eco-epidemiological regions. These findings underscore the importance of targeted public health interventions in reducing malarial morbidity and mortality rates in Colombia.

Malaria in a vulnerable population living in quilombo remnant communities in the Brazilian Amazon: a cross-sectional study from 2005-2020.

Quilombo remnant communities are areas officially recognized by the Brazilian government as historical communities founded by formerly enslaved individuals. These communities are mostly located in the endemic areas of malaria in the Brazilian Amazon. We retrospectively described the prevalence of malaria among individuals living in 32 recognized quilombo remnant communities in the Baiao and Oriximina municipalities located in the Para State. The number of malaria cases and the Annual Parasitic Incidence (API) recorded by the Brazilian malaria surveillance system (SIVEP-Malaria) from January 2005 to December 2020 were analyzed. We found that all communities registered at least one case over the 16-year period, the most frequent parasitic species being Plasmodium vivax (76.1%). During this period, 0.44% (4,470/1,008,714) of the malaria cases registered in Para State were reported in these quilombo remnant communities, with frequencies of 10.9% (856/7,859) in Baiao municipality and 39.1% (3,614/9,238) in Oriximina municipality, showing that individuals living in these rural communities are exposed to malaria. These data indicate that effective surveillance requires improved measures to identify malaria transmission among vulnerable populations living in quilombo remnant communities in the Brazilian Amazon.

Concurrent management of HIV and malaria: A comprehensive review of strategies to enhance quality of life.

The co-occurrence of human immunodeficiency virus and malaria presents a complex medical scenario, significantly impacting the quality of life for affected individuals. This comprehensive review synthesizes current knowledge, challenges, and strategies concerning the concurrent management of these infections to improve overall well-being. Epidemiological insights reveal the prevalence and demographic trends, highlighting geographical areas of concern and socioeconomic factors contributing to the burden of co-infection. Pathophysiological interactions elucidate the compounding effects, altering disease progression and treatment outcomes. Healthcare challenges underscore the necessity for integrated care models, evaluating existing healthcare frameworks and their efficacy in addressing dual infections. In-depth analysis of interventions explores pharmacological, behavioral, and preventive measures, evaluating their efficacy and safety in co-infected individuals. Additionally, the review assesses psychosocial support mechanisms, emphasizing community-based interventions and peer networks in enhancing holistic care. Consideration is given to the role of antiretroviral therapy, malaria prevention strategies, and the evolving landscape of healthcare delivery in optimizing outcomes for this vulnerable population. The paper concludes by emphasizing the significance of multidisciplinary approaches and integrated care models, stressing the need for continued research and collaborative efforts to advance interventions and improve the quality of life for those navigating the complexities of human immunodeficiency virus and malaria co-infection.