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

BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.

Gestational glucose intolerance among pregnant women at the Cape Coast Teaching Hospital.

BACKGROUND: Malaria in pregnancy can have adverse outcomes if untreated. Both malaria and pregnancy are associated with insulin resistance and diabetes. Although malaria is treated prophylactically with gestational diabetes mellitus (GDM) screened for in pregnancy as part a routine antenatal care, their impacts have not been examined in terms of other forms of dysglycaemia. This cross-sectional study examined insulin resistance and its relationship with dysglycaemia and malaria among pregnant women in the Cape Coast Teaching Hospital (CCTH). METHODS: Using a structured questionnaire, demographic and clinical information were obtained from 252 pregnant women aged 18-42 years. Weight and height were measured for computation of body mass index (BMI). Measurement of insulin, lipid profile and glucose were taken under fasting conditions followed by oral glucose tolerant test. Insulin resistance and beta-cell function were assessed by the homeostatic model as malaria was diagnosed by microscopy. RESULTS: The respective prevalence of GDM, gestational glucose intolerance (GGI) and insulin resistance were 0.8% (2/252), 19.44% (49/252) and 56.75% (143/252). No malaria parasite or dyslipidaemia was detected in any of the participants. Apart from BMI that increased across trimesters, no other measured parameter differed among the participants. Junior High School (JHS) education compared with no formal education increased the odds (AOR: 2.53; CI: 1.12-5.71; P = 0.03) but 2nd trimester of pregnancy compared to the 1st decreased the odds (AOR: 0.32; CI: 0.12-0.81; P = 0.02) of having insulin resistance in the entire sample. In a sub-group analysis across trimesters, pregnant women with JHS education in their 3rd trimester had increased odds (AOR: 4.41; CI: 1.25-15.62; P = 0.02) of having insulin resistance. CONCLUSION: Prevalence of GDM and GGI were 0.8% and 19.44% respectively. The odds of insulin resistance increased in pregnant women with JHS education in the 3rd trimester. Appropriate measures are needed to assuage the diabetogenic risk posed by GGI in our setting.

The relationship between anaemia and the use of treated bed nets among pregnant and non-pregnant women in Ghana.

Studies have indicated that the risk of malaria, particularly its association with anaemia in pregnant women, increases when treated bed nets are not used. This paper utilizes a statistical mechanical model to investigate whether there is a statistical relationship between the presence or absence of anaemia in pregnant and non-pregnant women and their decision to sleep under treated bed nets. Data from the Ghana Malaria Indicator Survey (GMIS), which includes both rural and urban malaria-endemic areas in Ghana, were employed in this study. A total of 2,434 women, comprising 215 pregnant and 2,219 non-pregnant participants, were involved. Among these, 4.76% of the pregnant and anaemic women and 45.89% of the non-pregnant and anaemic women slept under treated bed nets, while 0.86% of the pregnant and anaemic and 6.82% of the non-pregnant and anaemic women did not. The findings revealed that, in the absence of social interaction, non-anaemic pregnant women have a lower prevalence of choosing to use bed nets compared to their anaemic counterparts. Additionally, non-pregnant anaemic women showed a positive private incentive (30.87%) to use treated bed nets, implying a positive correlation between anaemia and the choice to sleep in a treated bed net. Furthermore, the study demonstrated that both pregnancy and anaemia status have a relationship with the use of treated bed nets in Ghana, especially when social interactions are considered. The interaction strength between non-pregnant and anaemic women interacting with each other shows a negative estimate (-1.49%), implying that there is no rewarding effect from imitation. These insights are crucial for malaria prevention and control programs, emphasizing the need for targeted interventions to enhance the use of treated bed nets among both pregnant and non-pregnant women in Ghana's malaria-endemic regions.

Distribution and dynamics of Anopheles gambiae s.l. larval habitats in three Senegalese cities with high urban malaria incidence.

Urban malaria has become a challenge for most African countries due to urbanization, with increasing population sizes, overcrowding, and movement into cities from rural localities. The rapid expansion of cities with inappropriate water drainage systems, abundance of water storage habitats, coupled with recurrent flooding represents a concern for water-associated vector borne diseases, including malaria. This situation could threaten progress made towards malaria elimination in sub-Saharan countries, including Senegal, where urban malaria has presented as a threat to national elimination gains. To assess drivers of urban malaria in Senegal, a 5-month study was carried out from August to December 2019 in three major urban areas and hotspots for malaria incidence (Diourbel, Touba, and Kaolack) including the rainy season (August-October) and partly dry season (November-December). The aim was to characterize malaria vector larval habitats, vector dynamics across both seasons, and to identify the primary eco- environmental entomological factors contributing to observed urban malaria transmission. A total of 145 Anopheles larval habitats were found, mapped, and monitored monthly. This included 32 in Diourbel, 83 in Touba, and 30 in Kaolack. The number of larval habitats fluctuated seasonally, with a decrease during the dry season. In Diourbel, 22 of the 32 monitored larval habitats (68.75%) were dried out by December and considered temporary, while the remaining 10 (31.25%) were classified as permanent. In the city of Touba 28 (33.73%) were temporary habitats, and of those 57%, 71% and 100% dried up respectively by October, November, and December. However, 55 (66.27%) habitats were permanent water storage basins which persisted throughout the study. In Kaolack, 12 (40%) permanent and 18 (60%) temporary Anopheles larval habitats were found and monitored during the study. Three malaria vectors (An. arabiensis, An. pharoensis and An. funestus s.l.) were found across the surveyed larval habitats, and An. arabiensis was found in all three cities and was the only species found in the city of Diourbel, while An. arabiensis, An. pharoensis, and An. funestus s.l. were detected in the cities of Touba and Kaolack. The spatiotemporal observations of immature malaria vectors in Senegal provide evidence of permanent productive malaria vector larval habitats year-round in three major urban centers in Senegal, which may be driving high urban malaria incidence. This study aimed to assess the presence and type of anopheline larvae habitats in urban areas. The preliminary data will better inform subsequent detailed additional studies and seasonally appropriate, cost-effective, and sustainable larval source management (LSM) strategies by the National Malaria Control Programme (NMCP).

Comparison of malaria diagnostic methods for detection of asymptomatic Plasmodium infections among pregnant women in northwest Ethiopia.

BACKGROUND: Malaria in pregnancy remains a major public health problem in the globe, especially in sub-Saharan Africa. In malaria endemic areas, most pregnant women remain asymptomatic, but malaria could still cause complications on the mother and her offspring; as well as serve as reservoirs to transmit infection. Despite these effects, no attention is given to the diagnosis of asymptomatic Plasmodium infections (APIs) using highly sensitive and specific laboratory diagnostic tools in Ethiopia. Therefore, the goal of this study was to compare the performance of Rapid Diagnostic Test (RDT), microscopy and real-time polymerase chain reaction (RT-PCR) to detect APIs among pregnant women. METHODS: A health facility based cross -sectional study was conducted among pregnant women attending antenatal care at Fendeka town health facilities Jawi district, northwest Ethiopia from February to March, 2019. A total of 166 participants were enrolled by using convenient sampling technique. Socio-demographic features were collected using a semi structured questionnaire. Dried blood spot (DBS) samples were collected for molecular analysis. Asymptomatic Plasmodium infection on pregnant women was diagnosed using RDT, microscopy and RT-PCR. Descriptive statistics were used to determine the prevalence of APIs. Method comparison was performed, and Cohen's kappa coefficient (k) was used to determine the degree of agreement among the diagnostic methods. Parasite densities were also calculated. RESULTS: The prevalence of API was 9.6%, 11.4% and 18.7% using RDT, microscopy and RT-PCR, respectively. The overall proportion of API was 19.3%. Sensitivity of the RDT was 83.3% as compared with microscopy. Rapid Diagnostic Test and microscopy also showed sensitivity of 50% and 60%, respectively, as compared with RT-PCR. The mean parasite density was 3213 parasites/µl for P falciparum and 1140 parasites/µl of blood for P. vivax. CONCLUSION: Prevalence of API in the study area was high. Both RDT and microscopy had lower sensitivity when compared with RT-PCR. Therefore, routine laboratory diagnosis of API among pregnant women should be given attention and done with better sensitive and specific laboratory diagnostic tools.

Prevalence of malaria and associated risk factors among household members in South Ethiopia: a multi-site cross-sectional study.

BACKGROUND: Despite continuous prevention and control strategies in place, malaria remains a major public health problem in sub-Saharan Africa including Ethiopia. Moreover, prevalence of malaria differs in different geographical settings and epidemiological data were inadequate to assure disease status in the study area. This study was aimed to determine the prevalence of malaria and associated risk factors in selected rural kebeles in South Ethiopia. METHODS: A community-based cross-sectional study was conducted between February to June 2019 in eight malaria-endemic kebeles situated in four zones in South Ethiopia. Mult-stage sampling techniques were employed to select the study zones, districts, kebeles and households. Blood sample were collected from 1674 participants in 345 households by finger prick and smears were examined by microscopy. Sociodemographic data as well as risk factors for Plasmodium infection were collected using questionnaires. Bivariate and multivariate logistic regressions were used to analyse the data. RESULTS: The overall prevalence of malaria in the study localities was 4.5% (76/1674). The prevalence was varied among the study localities with high prevalence in Bashilo (14.6%; 33/226) followed by Mehal Korga (12.1%; 26/214). Plasmodium falciparum was the dominant parasite accounted for 65.8% (50/76), while Plasmodium vivax accounted 18.4% (14/76). Co-infection of P. falciparum and P. vivax was 15.8% (12/76). Among the three age groups prevalence was 7.8% (27/346) in age less than 5 years and 7.5% (40/531) in 5-14 years. The age groups > 14years were less likely infected with Plasmodium parasite (AOR = 0.14, 95% CI 0.02-0.82) than under five children. Non-febrile individuals 1638 (97.8%) were more likely to had Plasmodium infection (AOR = 28.4, 95% CI 011.4-70.6) than febrile 36 (2.2%). Individuals living proximity to mosquito breeding sites have higher Plasmodium infection (AOR = 6.17, 95% CI 2.66-14.3) than those at distant of breeding sites. CONCLUSIONS: Malaria remains a public health problem in the study localities. Thus, malaria prevention and control strategies targeting children, non-febrile cases and individuals living proximity to breeding sites are crucial to reduce malaria related morbidity and mortality.

Modeling the effect of imported malaria on the elimination programme in KwaZulu-Natal province of South Africa.

Introduction: with imported malaria cases in a given population, the question arises as to what extent the local cases are a consequence of the imports or not. We perform a modeling analysis for a specific area, in a region aspiring for malaria-free status. Methods: data on malaria cases over ten years is subjected to a compartmental model which is assumed to be operating close to the equilibrium state. Two of the parameters of the model are fitted to the decadal data. The other parameters in the model are sourced from the literature. The model is utilized to simulate the malaria prevalence with or without imported cases. Results: in any given year the annual average of 460 imported cases, resulted in an end-of-year season malaria prevalence of 257 local active infectious cases, whereas without the imports the malaria prevalence at the end of the season would have been fewer than 10 active infectious cases. We calculate the numerical value of the basic reproduction number for the model, which reveals the extent to which the disease is being eliminated from the population or not. Conclusion: without the imported cases, over the ten seasons of malaria, 2008-2018, the KwaZulu-Natal province would have been malaria-free over at least the last 7 years of the decade indicated. This simple methodology works well even in situations where data is limited.

Factors associated with mosquito control among construction workers: A systematic review.

INTRODUCTION: Workers in the construction industry frequently work in construction sites with numerous areas that can potentially accumulate water, such as tanks, wet cement surfaces, or water puddles. These water collection sites become ideal breeding grounds for mosquito infestation, which leads to a higher prevalence of mosquito-borne diseases, especially malaria and dengue among construction workers. Despite that numerous factors have been identified in controlling vector-borne diseases, the specific factors that influence mosquito control at construction sites have yet to be explored. AIMS: This systematic review aims to determine the factors associated with mosquito control among construction workers. METHODS: Primarily, articles related to factors associated with mosquito control among construction workers were collected from two different online databases (ScienceDirect and EBSCOhost). Two independent reviewers were assigned to screen the titles and abstracts of the collected data, stored in Microsoft Excel, against the inclusion and exclusion criteria. Afterwards, the quality of the included articles was critically assessed using the Mixed Method Appraisal Tool (MMAT). Of the 171 articles identified, 4 were included in the final review. RESULTS: Based on the thorough evaluation, mosquito-related knowledge, practical mosquito prevention measures, and Larval Source Management (LSM) were identified as vital factors associated with mosquito control among construction workers. The significant association between mosquito-related knowledge and control practices indicates higher knowledge linked to effective practices, particularly among female workers and those who were recently infected with malaria. Concurrently, there were notable challenges regarding sustainable preventive measures and larval control methods in construction settings. CONCLUSION: Implementing effective mosquito control, including knowledge and practice on mosquito control together with vector control, is highly required to suppress the expanding mosquito population. It is recommended that employers provide continuous mosquito control education and training to their employees and reward them with incentives, while employees should comply with the guidelines set by their employers to ensure successful mosquito control and reduce the spread of mosquito-borne diseases in the construction industry.

Notes from the Field: Increases in Imported Malaria Cases - Three Southern U.S. Border Jurisdictions, 2023.

Malaria is a severe and potentially fatal mosquitoborne disease caused by infection with Plasmodium spp. parasites. Although malaria is no longer endemic in the United States, imported infections are reported annually; the primary risk group has been U.S. residents traveling to areas where malaria is endemic (1). In 2023, sporadic locally acquired mosquito-transmitted malaria cases were reported in several U.S. states (2,3). This report describes increases in imported malaria cases in 2023 compared with 2022 in three public health jurisdictions along the U.S. southern border.

Level of awareness and utilization of insecticide-treated bed nets among medical students as measures for reducing malaria episodes.

This study examined the level of awareness and utilization of insecticide-treated bed nets among medical students as measures for reducing malaria episodes in Delta State University, Abraka. It was a descriptive study with objectives and research questions formulated to achieve the study design. A sample size of 200 male and female students resident in the campus hostels were selected using random sampling technique. A self-structured questionnaire was designed and administered to the study participants, however, only 148 copies of the questionnaires were successfully retrieved and used for the study. Data generated were subjected to quantitative statistical analysis for frequencies, percentages, average mean and Chi-square testing. Findings revealed that the level of awareness was significantly associated with the role of health workers in the distribution of insecticide-treated bed nets in Delta State University, Abraka, although, factors hindering health workers from distributing insecticide-treated bed nets were identified. There was significant difference between perception of medical students and the utilization of insecticide-treated bed nets on risk of malaria spread. In addition, there was significant difference between the benefits of using insecticide-treated bed nets and the prevention and control of malaria. We therefore conclude that regular utilization of insecticide-treated bed nets due to adequate awareness eliminates contact with mosquitoes and prevents transmitting vectors of malaria from having contact with the users of insecticide-treated bed net. Massive health education campaign is recommended to further scale up the awareness and effective utilization of insecticide-treated bed nets towards prevention and control of malaria bites among students in Delta State University, Abraka.

The prevalence of Pfk13 polymorphism in malaria patients treated with artemisinin-based therapy: a systematic review and meta-analysis.

Artemisinin (ART) combination therapy is the main treatment for malaria. Pfk13 mutations (or K13 mutations, Kelch 13) are associated with ART resistance. This study aims to conduct a systematic review and meta-analysis of the prevalence of K13 mutations with ART resistance in malaria-endemic countries. An electronic search of studies in 2018 and a manual search in 2020 were performed to identify relevant studies. The risk of bias was assessed using the National Institutes of Health (NIH) quality assessment tool for observational cohort and cross-sectional studies. Data analysis was performed using R 4.1.0. Heterogeneity was estimated using the statistic I2 and Cochran Q test. A total of 170 studies were included in our review. Of these, 55 studies investigated the prevalence of K13 mutations in Southeast Asia. The meta-analysis showed that Southeast Asia had the highest prevalence of K13 mutations, whereas Africa, South America, Oceania, and other Asian countries outside Southeast Asia had a low prevalence of K13 mutations. The C580Y mutation was the most common in Southeast Asia with 35.5% (95%CI: 25.4-46.4%), whereas the dominant mutation in Africa was K189T (22.8%, 95%CI: 7.6-43.2%). This study revealed the emergence of ART resistance associated with K13 mutations in Southeast Asia. The diversity of each type of K13 mutation in other regions was also reported.

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.

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.

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.

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.

Spatio-temporal spread of artemisinin resistance in Southeast Asia.

Current malaria elimination targets must withstand a colossal challenge-resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially. Spatial information on the changing levels of artemisinin resistance in Southeast Asia is therefore critical for health organisations to prioritise malaria control measures, but available data on artemisinin resistance are sparse. We use a comprehensive database from the WorldWide Antimalarial Resistance Network on the prevalence of non-synonymous mutations in the Kelch 13 (K13) gene, which are known to be associated with artemisinin resistance, and a Bayesian geostatistical model to produce spatio-temporal predictions of artemisinin resistance. Our maps of estimated prevalence show an expansion of the K13 mutation across the Greater Mekong Subregion from 2000 to 2022. Moreover, the period between 2010 and 2015 demonstrated the most spatial change across the region. Our model and maps provide important insights into the spatial and temporal trends of artemisinin resistance in a way that is not possible using data alone, thereby enabling improved spatial decision support systems on an unprecedented fine-scale spatial resolution. By predicting for the first time spatio-temporal patterns and extents of artemisinin resistance at the subcontinent level, this study provides critical information for supporting malaria elimination goals in Southeast Asia.

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.

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.

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.

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.