The changing risk of Plasmodium falciparum malaria infection in Africa: 2000-10: a spatial and temporal analysis of transmission intensity

Epidemiological feature of imported malaria in Taiwan during the 2014-to-2020 period

Although the World Health Organization (WHO) certified Taiwan as being malaria-free in 1965, there are reports of a few imported cases each year by travelers who visit malaria-endemic areas. This study examined the epidemiology of imported malaria cases in Taiwan from 2014 to 2020, utilizing national surveillance data from the Taiwan Centers for Disease Control. Malaria cases were confirmed through the application of standard laboratory methods. Passenger data came from the Tourism Bureau, Ministry of Transportation and Communication, Taiwan (TBMTC). All data were analyzed using SPSS version 21. The analysis included a dataset comprising 64 cases of imported malaria. Of the total cases, 77.8% were acquired from Africa, and 17.5% from Asia. Plasmodium falciparum was responsible for more than half (57.1%) of the cases, Plasmodium vivax malaria for 25.4% of cases, Plasmodium malariae malaria for 6.3%, Plasmodium ovale malaria for 4.8%, and unspecified pathogen malaria for 6.3% of the cases. Majority of the patients were male (75%) and were predominantly aged 20 to 59 years (70.3%). Most cases of imported malaria occurred during the fall season, and 51.6% of cases occurred in 8 cities during the period of 2014 to 2020. No evidence exists to indicate that indigenous malaria transmission occurs in Taiwan. Anopheles minimus was found in 4 cities (counties), namely Tainan City and Pingtung County in Southern Taiwan; Hualien County and Taitung County in Eastern Taiwan. The findings of this study highlight the necessity for robust surveillance systems, effective vector control measures, and targeted interventions for travelers and immigrants to prevent malaria outbreaks and maintain Taiwan's malaria-free status.

Higher temperatures and being an ethnic minority reduce mosquito net use in Lao PDR: an analysis of Lao PDR's Multiple Indicator Cluster Survey and Earth observation satellite data

BACKGROUND

Malaria remains the leading cause of under-five morbidity and mortality in low- and middle-income countries. Sleeping under mosquito nets, especially insecticide-treated nets (ITNs), is one of the best ways to prevent malaria as they form a physical and chemical barrier against mosquitoes. Therefore, the present study aimed to assess not only mosquito net use, but also how environmental factors, specifically land surface temperature, contribute to malaria prevention among households with children under 5 years of age in Lao PDR.

METHODS

The most recent Multiple Indicator Cluster Survey datasets of Lao PDR 2017 and the Japan Aerospace Exploration Agency (JAXA) Public Health Monitoring and Analysis Platform (JPMAP) were used. Data from 51,948 households were used in the analysis. A bivariate logistic regression analysis was followed by a multivariate logistic regression analysis to determine the factors influencing mosquito net use with children under five.

RESULTS

In this study, 77.8% of all households with children under 5 years of age slept under mosquito nets. Of these, 80.5% were ITNs (Olyset, Permanent, and other brands). Multivariate logistic regression analysis revealed that mosquito net use was significantly associated with the land surface temperature, ethno-linguistic group (Lao-Tai, Mon-Khmer, Hmong-Mien, Chinese-Tibetan, and other), education level of the household head, and wealth index quintile.

CONCLUSIONS

The analysis of the present study suggested measures to intensify the use of mosquito nets with an emphasis on ethnic minorities living in hot areas to bring Lao PDR closer to the day that mosquito-borne infections such as malaria can be eliminated.

A century of medical records reveal earlier onset of the malaria season in Haut-Katanga induced by climate change

BACKGROUND

Despite worldwide efforts to eradicate malaria over the past century, the disease remains a significant challenge in the Democratic Republic of the Congo (DRC) today. Climate change is even anticipated to worsen the situation in areas with higher altitudes and vulnerable populations. This study in Haut-Katanga, a highland region, aims to evaluate the effectiveness of past control measures and to explore the impact of climate change on the region's distinct seasonal malaria pattern throughout the last century.

METHODS

We integrated colonial medical records (1917-1983) from two major mining companies (Union Minière du Haut-Katanga and the Générale des Carrières et des Mines) with contemporary data (2003-2020) from Lubumbashi. Concurrently, we combined colonial climate records (1912-1946) with recent data from satellite images and weather stations (1940-2023). We used Generalised Additive Models to link the two data sources and to test for changing seasonal patterns in transmission.

RESULTS

Malaria transmission in Haut-Katanga has fluctuated significantly over the past century, influenced by evolving control strategies, political conditions and a changing climate. A notable decrease in cases followed the introduction of dichlorodiphenyltrichloroethane (DDT), while a surge occurred after the civil wars ended at the beginning of the new millennium. Recently, the malaria season began 1-2 months earlier than historically observed, likely due to a 2-5°C increase in mean minimum temperatures, which facilitates the sporogonic cycle of the parasite.

CONCLUSION

Despite contemporary control efforts, malaria incidence in Haut-Katanga is similar to levels observed in the 1930s, possibly influenced by climate change creating optimal conditions for malaria transmission. Our historical data shows that the lowest malaria incidence occurred during periods of intensive DDT use and indoor residual spraying. Consequently, we recommend the systematic reduction of vector populations as a key component of malaria control strategies in highland regions of sub-Saharan Africa.

SEVUparin as a potential Adjunctive Treatment in children with severe malaria: A phase I trial safety and dose finding trial (SEVUSMAART)

Background

Even on the best antimalarial treatments (injectable artesunate) African children with severe malaria have poor outcomes with most deaths occurring early in the course of hospital admission (<24hours). Lactic acidosis, largely due to impairment of the microcirculatory flow due to parasite sequestration, is a main risk factor for poor outcome. There are no adjuvant treatments for severe malaria that target this complication. Sevuparin, a heparin-like drug, binds to Plasmodium falciparum erythrocyte membrane protein blocking merozoite invasion, preventing cytoadherence and transiently de-sequestering infected erythrocytes. Leading to improved microcirculatory flow by reversing/preventing parasite sequestration. If given early during admission this could result in improvements in outcomes. Sevuparin has been shown to be safe and well tolerated in adults with only some mild transient effects on activated partial thromboplastin time (APTT) were reported, without clinical consequences.

Methods

A Phase I trial designed to provide data on safety, dosing, feasibility of sevuparin as an adjuvant therapy in Kenya and Zambian children with severe malaria complicated by lactic acidosis (> 2mmol/l). Three intravenous doses will be given at admission (0 hours), 8 and 16 hours. APPT will be measured 1 hour after each dose (to assess maximum toxicity). Studying 20 children will allow sufficient data on safety to be generated across a range of doses to identify the maximum tolerated dose (MTD) using the Continual Reassessment Method, which adapts or informs subsequent doses for each child based on the data from previously enrolled children. The MTD will be identified based on the dose-toxicity model updated by each previous patient's APTT results using standard methods.

Conclusions

The results of the Phase I trial will identify the final dose to be tested in a Phase II trial in terms of both efficacy and safety outcomes.

Registration

PACTR number: 202007890194806 (date 20/07/2020) ISRCTN32271864 (date 28/07/2021).

Urbanization and malaria have a contextual relationship in endemic areas: A temporal and spatial study in Ghana

In West Africa, malaria is one of the leading causes of disease-induced deaths. Existing studies indicate that as urbanization increases, there is corresponding decrease in malaria prevalence. However, in malaria-endemic areas, the prevalence in some rural areas is sometimes lower than in some peri-urban and urban areas. Therefore, the relationship between the degree of urbanization, the impact of living in urban areas, and the prevalence of malaria remains unclear. This study explores this association in Ghana, using epidemiological data at the district level (2015-2018) and data on health, hygiene, and education. We applied a multilevel model and time series decomposition to understand the epidemiological pattern of malaria in Ghana. Then we classified the districts of Ghana into rural, peri-urban, and urban areas using administratively defined urbanization, total built areas, and built intensity. We converted the prevalence time series into cross-sectional data for each district by extracting features from the data. To predict the determinant most impacting according to the degree of urbanization, we used a cluster-specific random forest. We find that prevalence is impacted by seasonality, but the trend of the seasonal signature is not noticeable in urban and peri-urban areas. While urban districts have a slightly lower prevalence, there are still pockets with higher rates within these regions. These areas of high prevalence are linked to proximity to water bodies and waterways, but the rise in these same variables is not associated with the increase of prevalence in peri-urban areas. The increase in nightlight reflectance in rural areas is associated with an increased prevalence. We conclude that urbanization is not the main factor driving the decline in malaria. However, the data indicate that understanding and managing malaria prevalence in urbanization will necessitate a focus on these contextual factors. Finally, we design an interactive tool, 'malDecision' that allows data-supported decision-making.

Bayesian spatio-temporal analysis of malaria prevalence in children between 2 and 10 years of age in Gabon

BACKGROUND

Gabon still bears significant malaria burden despite numerous efforts. To reduce this burden, policy-makers need strategies to design effective interventions. Besides, malaria distribution is well known to be related to the meteorological conditions. In Gabon, there is limited knowledge of the spatio-temporal effect or the environmental factors on this distribution. This study aimed to investigate on the spatio-temporal effects and environmental factors on the distribution of malaria prevalence among children 2-10 years of age in Gabon.

METHODS

The study used cross-sectional data from the Demographic Health Survey (DHS) carried out in 2000, 2005, 2010, and 2015. The malaria prevalence was obtained by considering the weighting scheme and using the space-time smoothing model. Spatial autocorrelation was inferred using the Moran's I index, and hotspots were identified with the local statistic Getis-Ord General Gi. For the effect of covariates on the prevalence, several spatial methods implemented in the Integrated Nested Laplace Approximation (INLA) approach using Stochastic Partial Differential Equations (SPDE) were compared.

RESULTS

The study considered 336 clusters, with 153 (46%) in rural and 183 (54%) in urban areas. The prevalence was highest in the Estuaire province in 2000, reaching 46%. It decreased until 2010, exhibiting strong spatial correlation (P < 0.001), decreasing slowly with distance. Hotspots were identified in north-western and western Gabon. Using the Spatial Durbin Error Model (SDEM), the relationship between the prevalence and insecticide-treated bed nets (ITNs) coverage was decreasing after 20% of coverage. The prevalence in a cluster decreased significantly with the increase per percentage of ITNs coverage in the nearby clusters, and per degree Celsius of day land surface temperature in the same cluster. It slightly increased with the number of wet days and mean temperature per month in neighbouring clusters.

CONCLUSIONS

In summary, this study showed evidence of strong spatial effect influencing malaria prevalence in household clusters. Increasing ITN coverage by 20% and prioritizing hotspots are essential policy recommendations. The effects of environmental factors should be considered, and collaboration with the national meteorological department (DGM) for early warning systems is needed.

Plasmodium falciparum population structure and genetic diversity of cell traversal protein for ookinetes and sporozoites (CelTOS) during malaria resurgences in Dielmo, Senegal

The ability to accurately measure the intensity of malaria transmission in areas with low transmission is extremely important to guide elimination efforts. Plasmodium falciparum Cell-traversal protein for ookinetes and sporozoites (PfCelTOS) is an important conserved sporozoite antigen reported as one of the promising malaria vaccine candidates, and could be used to estimate malaria transmission intensity. This study aimed at determining whether the diversity of PfCelTOS gene reflects the changes in malaria transmission that occurred between 2007 and 2014 in Dielmo, a Senegalese village, before and after the implementation of insecticide treated bed nets (ITNs). Of the 109 samples positive for PfCelTOS PCR, 96 (88%) were successfully sequenced and analysed for polymorphisms and population diversity. The number of segregating sites was higher during the pre-intervention period (13) and the malaria resurgences (11) than during the intervention period (5). Similarly, the number and diversity of haplotypes were higher during the pre-intervention period (16 and 0.914, respectively) and the malaria resurgences (6 and 0.821, respectively) than during the intervention period (4 and 0.758, respectively). Moreover, the average number of nucleotide differences was higher during the pre-intervention (3.792) and during malaria resurgences (3.467) than during the intervention period (2.189). The 3D7 KSSFNEP haplotype was only observed during the intervention period. Only two haplotypes were shared in both the pre-intervention and intervention periods while four haplotypes were shared between the pre-intervention and the malaria resurgences. The Fst values indicate moderate differentiation between pre-intervention and intervention periods (0.17433), and between intervention and malaria resurgences period (0.19198) as well as between pre-intervention and malaria resurgences periods (0.06607). PfCelTOS genetic diversity reflected changes of malaria transmission, with higher polymorphisms recorded before the large-scale implementation of ITNs and during the malaria resurgences. PfCelTOS is also a candidate vaccine; mapping its diversity across multiple endemic environments will facilitate the design and optimisation of a broad and efficacious vaccine.

Comparison of new computational methods for spatial modelling of malaria

BACKGROUND

Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes. The appeal of faster methods is particularly great as the size of the region and number of spatial locations being modelled increases.

METHODS

This work presents an applied comparison of four proposed 'fast' computational methods for spatial modelling and the software provided to implement them-Integrated Nested Laplace Approximation (INLA), tree boosting with Gaussian processes and mixed effect models (GPBoost), Fixed Rank Kriging (FRK) and Spatial Random Forests (SpRF). The four methods are illustrated by estimating malaria prevalence on two different spatial scales-country and continent. The performance of the four methods is compared on these data in terms of accuracy, computation time, and ease of implementation.

RESULTS

Two of these methods-SpRF and GPBoost-do not scale well as the data size increases, and so are likely to be infeasible for larger-scale analysis problems. The two remaining methods-INLA and FRK-do scale well computationally, however the resulting model fits are very sensitive to the user's modelling assumptions and parameter choices. The binomial observation distribution commonly used for disease prevalence mapping with INLA fails to account for small-scale overdispersion present in the malaria prevalence data, which can lead to poor predictions. Selection of an appropriate alternative such as the Beta-binomial distribution is required to produce a reliable model fit. The small-scale random effect term in FRK overcomes this pitfall, but FRK model estimates are very reliant on providing a sufficient number and appropriate configuration of basis functions. Unfortunately the computation time for FRK increases rapidly with increasing basis resolution.

CONCLUSIONS

INLA and FRK both enable scalable geostatistical modelling of malaria prevalence data. However care must be taken when using both methods to assess the fit of the model to data and plausibility of predictions, in order to select appropriate model assumptions and parameters.

Distribution of Plasmodium falciparum K13 gene polymorphisms across transmission settings in Ghana

Malaria is a significant global health concern, with a majority of cases in Sub-Saharan African nations. Numerous antimalarial drugs have been developed to counter the rampant prevalence of Plasmodium falciparum malaria. Artemisinin-based Combination Therapy (ACT) has served as the primary treatment of uncomplicated malaria in Ghana since 2005. However, a growing concern has emerged due to the escalating reports of ACT resistance, particularly in Southeast Asia, and its encroachment into Africa. Specifically, mutations in the Kelch propeller domain on chromosome 13 (Pfk13) have been linked to ACT resistance. Yet, our understanding of mutation prevalence in Africa remains largely uncharted. In this study, we compared Pfk13 sequences obtained from 172 P. falciparum samples across three ecological and transmission zones in Ghana. We identified 27 non-synonymous mutations among these sequences, of which two of the mutations, C580Y (found in two samples from the central region) and Y493H (found in one sample from the north), had previously been validated for their association with artemisinin resistance, a phenomenon widespread in Southeast Asia. The Pfk13 gene diversity was most pronounced in the northern savannah than the central forest and south coastal regions, where transmission rates are lower. The observed mutations were not significantly associated with geographical regions, suggesting a frequent spread of mutations across the country. The ongoing global surveillance of artemisinin resistance remains pivotal, and our findings provides insights into the potential spread of resistant parasites in West Africa. Furthermore, the identification of novel codon mutations in this study raises their potential association to ACT resistance, warranting further investigation through in vitro assays to ascertain their functional significance.

Anopheles vector distribution and malaria transmission dynamics in Gbêkê region, central Côte d'Ivoire

BACKGROUND

A better understanding of vector distribution and malaria transmission dynamics at a local scale is essential for implementing and evaluating effectiveness of vector control strategies. Through the data gathered in the framework of a cluster randomized controlled trial (CRT) evaluating the In2Care (Wageningen, Netherlands) Eave Tubes strategy, the distribution of the Anopheles vector, their biting behaviour and malaria transmission dynamics were investigated in Gbêkê region, central Côte d'Ivoire.

METHODS

From May 2017 to April 2019, adult mosquitoes were collected monthly using human landing catches (HLC) in twenty villages in Gbêkê region. Mosquito species wereidentified morphologically. Monthly entomological inoculation rates (EIR) were estimated by combining the HLC data with mosquito sporozoite infection rates measured in a subset of Anopheles vectors using PCR. Finally, biting rate and EIR fluctuations were fit to local rainfall data to investigate the seasonal determinants of mosquito abundance and malaria transmission in this region.

RESULTS

Overall, Anopheles gambiae, Anopheles funestus, and Anopheles nili were the three vector complexes found infected in the Gbêkê region, but there was a variation in Anopheles vector composition between villages. Anopheles gambiae was the predominant malaria vector responsible for 84.8% of Plasmodium parasite transmission in the area. An unprotected individual living in Gbêkê region received an average of 260 [222-298], 43.5 [35.8-51.29] and 3.02 [1.96-4] infected bites per year from An. gambiae, An. funestus and An. nili, respectively. Vector abundance and malaria transmission dynamics varied significantly between seasons and the highest biting rate and EIRs occurred in the months of heavy rainfall. However, mosquitoes infected with malaria parasites remained present in the dry season, despite the low density of mosquito populations.

CONCLUSION

These results demonstrate that the intensity of malaria transmission is extremely high in Gbêkê region, especially during the rainy season. The study highlights the risk factors of transmission that could negatively impact current interventions that target indoor control, as well as the urgent need for additional vector control tools to target the population of malaria vectors in Gbêkê region and reduce the burden of the disease.

Pharmacokinetics and pharmacodynamics of azithromycin in severe malaria bacterial co-infection in African children (TABS-PKPD): a protocol for a Phase II randomised controlled trial

Background: African children with severe malaria are susceptible to Gram-negative bacterial co-infection, largely non-typhoidal Salmonellae, leading to a substantially higher rates of in-hospital and post-discharge mortality than those without bacteraemia. Current evidence for treating co-infection is lacking, and there is no consensus on the dosage or length of treatment required. We therefore aimed to establish the appropriate dose of oral dispersible azithromycin as an antimicrobial treatment for children with severe malaria and to investigate whether antibiotics can be targeted to those at greatest risk of bacterial co-infection using clinical criteria alone or in combination with rapid diagnostic biomarker tests. Methods: A Phase I/II open-label trial comparing three doses of azithromycin: 10, 15 and 20 mg/kg spanning the lowest to highest mg/kg doses previously demonstrated to be equally effective as parenteral treatment for other salmonellae infection. Children with the highest risk of bacterial infection will receive five days of azithromycin and followed for 90 days. We will generate relevant pharmacokinetic data by sparse sampling during dosing intervals. We will use population pharmacokinetic modelling to determine the optimal azithromycin dose in severe malaria and investigate azithromycin exposure to change in C-reactive protein, a putative marker of sepsis at 72 hours, and microbiological cure (seven-day), alone and as a composite with seven-day survival. We will also evaluate whether a combination of clinical, point-of-care diagnostic tests, and/or biomarkers can accurately identify the sub-group of severe malaria with culture-proven bacteraemia by comparison with a control cohort of children hospitalized with severe malaria at low risk of bacterial co-infection. Discussion: We plan to study azithromycin because of its favourable microbiological spectrum, its inherent antimalarial and immunomodulatory properties and dosing and safety profile. This study will generate new data to inform the design and sample size for definitive Phase III trial evaluation. Registration: ISRCTN49726849 (27 th October 2017).

Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors: Evidence from rural Madagascar

While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.

The use of routine health facility data for micro-stratification of malaria risk in mainland Tanzania

Background

Current efforts to estimate the spatially diverse malaria burden in malaria-endemic countries largely involve the use of epidemiological modelling methods for describing temporal and spatial heterogeneity using sparse interpolated prevalence data from periodic cross-sectional surveys. However, more malaria-endemic countries are beginning to consider local routine data for this purpose. Nevertheless, routine information from health facilities (HFs) remains widely under-utilized despite improved data quality, including increased access to diagnostic testing and the adoption of the electronic District Health Information System (DHIS2). This paper describes the process undertaken in mainland Tanzania using routine data to develop a high-resolution, micro-stratification risk map to guide future malaria control efforts.

Methods

Combinations of various routine malariometric indicators collected from 7098 HFs were assembled across 3065 wards of mainland Tanzania for the period 2017–2019. The reported council-level prevalence classification in school children aged 5–16 years (PfPR5–16) was used as a benchmark to define four malaria risk groups. These groups were subsequently used to derive cut-offs for the routine indicators by minimizing misclassifications and maximizing overall agreement. The derived-cutoffs were converted into numbered scores and summed across the three indicators to allocate wards into their overall risk stratum.

Results

Of 3065 wards, 353 were assigned to the very low strata (10.5% of the total ward population), 717 to the low strata (28.6% of the population), 525 to the moderate strata (16.2% of the population), and 1470 to the high strata (39.8% of the population). The resulting micro-stratification revealed malaria risk heterogeneity within 80 councils and identified wards that would benefit from community-level focal interventions, such as community-case management, indoor residual spraying and larviciding.

Conclusion

The micro-stratification approach employed is simple and pragmatic, with potential to be easily adopted by the malaria programme in Tanzania. It makes use of available routine data that are rich in spatial resolution and that can be readily accessed allowing for a stratification of malaria risk below the council level. Such a framework is optimal for supporting evidence-based, decentralized malaria control planning, thereby improving the effectiveness and allocation efficiency of malaria control interventions.

Malaria attributable fractions with changing transmission intensity: Bayesian latent class vs logistic models

Background

Asymptomatic carriage of malaria parasites is common in high transmission intensity areas and confounds clinical case definitions for research studies. This is important for investigations that aim to identify immune correlates of protection from clinical malaria. The proportion of fevers attributable to malaria parasites is widely used to define different thresholds of parasite density associated with febrile episodes. The varying intensity of malaria transmission was investigated to check whether it had a significant impact on the parasite density thresholds. The same dataset was used to explore an alternative statistical approach, using the probability of developing fevers as a choice over threshold cut-offs. The former has been reported to increase predictive power.

Methods

Data from children monitored longitudinally between 2005 and 2017 from Junju and Chonyi in Kilifi, Kenya were used. Performance comparison of Bayesian-latent class and logistic power models in estimating malaria attributable fractions and probabilities of having fever given a parasite density with changing malaria transmission intensity was done using Junju cohort. Zero-inflated beta regressions were used to assess the impact of using probabilities to evaluate anti-merozoite antibodies as correlates of protection, compared with multilevel binary regression using data from Chonyi and Junju.

Results

Malaria transmission intensity declined from over 49% to 5% between 2006 and 2017, respectively. During this period, malaria attributable fraction varied between 27–59% using logistic regression compared to 10–36% with the Bayesian latent class approach. Both models estimated similar patterns of fevers attributable to malaria with changing transmission intensities. The Bayesian latent class model performed well in estimating the probabilities of having fever, while the latter was efficient in determining the parasite density threshold. However, compared to the logistic power model, the Bayesian algorithm yielded lower estimates for both attributable fractions and probabilities of fever. In modelling the association of merozoite antibodies and clinical malaria, both approaches resulted in comparable estimates, but the utilization of probabilities had a better statistical fit.

Conclusions

Malaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.

Combining school-catchment area models with geostatistical models for analysing school survey data from low-resource settings: Inferential benefits and limitations

School-based sampling has been used to inform targeted responses for malaria and neglected tropical diseases. Standard geostatistical methods for mapping disease prevalence use the school location to model spatial correlation, which is questionable since exposure to the disease is more likely to occur in the residential location. In this paper, we propose to overcome the limitations of standard geostatistical methods by introducing a modelling framework that accounts for the uncertainty in the location of the residence of the students. By using cost distance and cost allocation models to define spatial accessibility and in absence of any information on the travel mode of students to school, we consider three school catchment area models that assume walking only, walking and bicycling and, walking and motorized transport. We illustrate the use of this approach using two case studies of malaria in Kenya and compare it with the standard approach that uses the school locations to build geostatistical models. We argue that the proposed modelling framework presents several inferential benefits, such as the ability to combine data from multiple surveys some of which may also record the residence location, and to deal with ecological bias when estimating the effects of malaria risk factors. However, our results show that invalid assumptions on the modes of travel to school can worsen the predictive performance of geostatistical models. Future research in this area should focus on collecting information on the modes of transportation to school which can then be used to better parametrize the catchment area models.

Bayesian spatial modelling of malaria burden in two contrasted eco-epidemiological facies in Benin (West Africa): call for localized interventions

Background

Despite a global decrease in malaria burden worldwide, malaria remains a major public health concern, especially in Benin children, the most vulnerable group. A better understanding of malaria’s spatial and age-dependent characteristics can help provide durable disease control and elimination. This study aimed to analyze the spatial distribution of Plasmodium falciparum malaria infection and disease among children under five years of age in Benin, West Africa.

Methods

A cross-sectional epidemiological and clinical survey was conducted using parasitological examination and rapid diagnostic tests (RDT) in Benin. Interviews were done with 10,367 children from 72 villages across two health districts in Benin. The prevalence of infection and clinical cases was estimated according to age. A Bayesian spatial binomial model was used to estimate the prevalence of malaria infection, and clinical cases were adjusted for environmental and demographic covariates. It was implemented in R using Integrated Nested Laplace Approximations (INLA) and Stochastic Partial Differentiation Equations (SPDE) techniques.

Results

The prevalence of P. falciparum infection was moderate in the south (34.6%) of Benin and high in the northern region (77.5%). In the south, the prevalence of P. falciparum infection and clinical malaria cases were similar according to age. In northern Benin children under six months of age were less frequently infected than children aged 6–11, 12–23, 24–60 months, (p < 0.0001) and had the lowest risk of malaria cases compared to the other age groups (6–12), (13–23) and (24–60): OR = 3.66 [2.21–6.05], OR = 3.66 [2.21–6.04], and OR = 2.83 [1.77–4.54] respectively (p < 0.0001). Spatial model prediction showed more heterogeneity in the south than in the north but a higher risk of malaria infection and clinical cases in the north than in the south.

Conclusion

Integrated and periodic risk mapping of Plasmodium falciparum infection and clinical cases will make interventions more evidence-based by showing progress or a lack in malaria control.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14032-9.

Fucoxanthin: A Promising Phytochemical on Diverse Pharmacological Targets

Fucoxanthin (FX) is a special carotenoid having an allenic bond in its structure. FX is extracted from a variety of algae and edible seaweeds. It has been proved to contain numerous health benefits and preventive effects against diseases like diabetes, obesity, liver cirrhosis, malignant cancer, etc. Thus, FX can be used as a potent source of both pharmacological and nutritional ingredient to prevent infectious diseases. In this review, we gathered the information regarding the current findings on antimicrobial, antioxidant, anti-inflammatory, skin protective, anti-obesity, antidiabetic, hepatoprotective, and other properties of FX including its bioavailability and stability characteristics. This review aims to assist further biochemical studies in order to develop further pharmaceutical assets and nutritional products in combination with FX and its various metabolites.

Mapping ex ante risks of COVID-19 in Indonesia using a Bayesian geostatistical model on airport network data

A rapid response to global infectious disease outbreaks is crucial to protect public health. Ex ante information on the spatial probability distribution of early infections can guide governments to better target protection efforts. We propose a two-stage statistical approach to spatially map the ex ante importation risk of COVID-19 and its uncertainty across Indonesia based on a minimal set of routinely available input data related to the Indonesian flight network, traffic and population data, and geographical information. In a first step, we use a generalised additive model to predict the ex ante COVID-19 risk for 78 domestic Indonesian airports based on data from a global model on the disease spread and covariates associated with Indonesian airport network flight data prior to the global COVID-19 outbreak. In a second step, we apply a Bayesian geostatistical model to propagate the estimated COVID-19 risk from the airports to all of Indonesia using freely available spatial covariates including traffic density, population and two spatial distance metrics. The results of our analysis are illustrated using exceedance probability surface maps, which provide policy-relevant information accounting for the uncertainty of the estimates on the location of areas at risk and those that might require further data collection.

Outdoor biting and pyrethroid resistance as potential drivers of persistent malaria transmission in Zanzibar

BACKGROUND

Low-level of malaria transmission persist in Zanzibar despite high coverage of core vector control interventions. This study was carried out in hot-spot sites to better understand entomological factors that may contribute to residual malaria transmission in Zanzibar.

METHODS

A total of 135 households were randomly selected from six sites and consented to participate with 20-25 households per site. Mosquito vector surveillance was carried out indoors and outdoors from 6:00 pm-7:00 am using miniaturized double net trap (DN-Mini™). Additional collections were done indoors using mouth aspirators to retrieve resting mosquitoes from wall and ceiling surfaces, and outdoors using resting bucket and pit traps. All collected mosquitoes were morphologically and genetically (PCR) analysed in the laboratory. All collected anopheline and blood-fed mosquitoes were analysed for sporozoite infection and blood meal host preferences by Circumsporozoite Protein ELISA and blood meal ELISA, respectively. The differences between indoor and outdoor mosquito biting rates were analysed using generalized linear mixed models. Levels of resistance to commonly used insecticides were quantified by WHO susceptibility tests.

RESULTS

Out of 704 malaria vectors collected across 135 households, PCR analysis shows that 98.60% were Anopheles arabiensis, 0.6% Anopheles merus and 0.6% Anopheles gambiae sensu stricto. Sporozoite ELISA analysis indicates that all mosquitoes were negative for the malaria parasite. The results show that more An. arabiensis were collected outdoor (~ 85%) compared to indoor (~ 15%). Furthermore, large numbers of An. arabiensis were caught in outdoor resting sites, where the pit trap (67.2%) collected more mosquitoes compared to the outdoor DN-Mini trap (32.8%). Nearly two-thirds (60.7%) of blood-fed mosquitoes had obtained blood meals from non-human hosts. Mosquitoes displayed non-uniform susceptibility status and resistance intensity among the tested insecticides across the study sites to all WHO recommended insecticides across the study sites.

CONCLUSION

This study suggests that in contexts such as Zanzibar, testing of novel techniques to complement indoor protection and targeting outdoor biting and/or resting mosquitoes, may be warranted to complement existing interventions and contribute to malaria elimination efforts. The study highlights the need to implement novel interventions and/or adaptations of strategies that can target outdoors biting mosquitoes.

Predictors of Plasmodium falciparum Infection in the First Trimester Among Nulliparous Women From Kenya, Zambia, and the Democratic Republic of the Congo

BACKGROUND

Malaria can have deleterious effects early in pregnancy, during placentation. However, malaria testing and treatment are rarely initiated until the second trimester, leaving pregnancies unprotected in the first trimester. To inform potential early intervention approaches, we sought to identify clinical and demographic predictors of first-trimester malaria.

METHODS

We prospectively recruited women from sites in the Democratic Republic of the Congo (DRC), Kenya, and Zambia who participated in the ASPIRIN (Aspirin Supplementation for Pregnancy Indicated risk Reduction In Nulliparas) trial. Nulliparous women were tested for first-trimester Plasmodium falciparum infection by quantitative polymerase chain reaction. We evaluated predictors using descriptive statistics.

RESULTS

First-trimester malaria prevalence among 1513 nulliparous pregnant women was 6.3% (95% confidence interval [CI], 3.7%-8.8%] in the Zambian site, 37.8% (95% CI, 34.2%-41.5%) in the Kenyan site, and 62.9% (95% CI, 58.6%-67.2%) in the DRC site. First-trimester malaria was associated with shorter height and younger age in Kenyan women in site-stratified analyses, and with lower educational attainment in analyses combining all 3 sites. No other predictors were identified.

CONCLUSIONS

First-trimester malaria prevalence varied by study site in sub-Saharan Africa. The absence of consistent predictors suggests that routine parasite screening in early pregnancy may be needed to mitigate first-trimester malaria in high-prevalence settings.

Distribution of bacteriologically positive and bacteriologically negative pulmonary tuberculosis in Northwest China: spatiotemporal analysis

Pulmonary tuberculosis (PTB) is a major health issue in Northwest China. Most previous studies on the spatiotemporal patterns of PTB considered all PTB cases as a whole; they did not distinguish notified bacteriologically positive PTB (BP-PTB) and notified bacteriologically negative PTB (BN-PTB). Thus, the spatiotemporal characteristics of notified BP-PTB and BN-PTB are still unclear. A retrospective county-level spatial epidemiological study (2011-2018) was conducted in Shaanxi, Northwest China. In total, 44,894 BP-PTB cases were notified, with an average annual incidence rate of 14.80 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BP-PTB ranged from 0.19 to 0.49 (P < 0.001). Anselin's local Moran's I analysis showed that the high-high (HH) cluster for notified BP-PTB incidence was mainly located in the southernmost region. The primary spatiotemporal cluster for notified BP-PTB (LLR = 612.52, RR = 1.77, P < 0.001) occurred in the central region of the Guanzhong Plain in 2011. In total, 116,447 BN-PTB cases were notified, with an average annual incidence rate of 38.38 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BN-PTB ranged from 0.39 to 0.69 (P < 0.001). The HH clusters of notified BN-PTB were mainly located in the north between 2011 and 2014 and in the south after 2015. The primary spatiotemporal cluster for notified BN-PTB (LLR = 1084.59, RR = 1.85, P < 0.001) occurred in the mountainous areas of the southernmost region from 2014 to 2017. Spatiotemporal clustering of BP-PTB and BN-PTB was detected in the poverty-stricken mountainous areas of Shaanxi, Northwest China. Our study provides evidence for intensifying PTB control activities in these geographical clusters.

Evaluating malaria prevalence and land cover across varying transmission intensity in Tanzania using a cross-sectional survey of school-aged children

BACKGROUND

Transmission of malaria in sub-Saharan Africa has become increasingly stratified following decades of malaria control interventions. The extent to which environmental and land cover risk factors for malaria may differ across distinct strata of transmission intensity is not well known and could provide actionable targets to maximize the success of malaria control efforts.

METHODS

This study used cross-sectional malaria survey data from a nationally representative cohort of school-aged children in Tanzania, and satellite-derived measures for environmental features and land cover. Hierarchical logistic regression models were applied to evaluate associations between land cover and malaria prevalence within three distinct strata of transmission intensity: low and unstable, moderate and seasonal, and high and perennial.

RESULTS

In areas with low malaria transmission, each 10-percentage point increase in cropland cover was associated with an increase in malaria prevalence odds of 2.44 (95% UI: 1.27, 5.11). However, at moderate and higher levels of transmission intensity, no association between cropland cover and malaria prevalence was detected. Small associations were observed between greater grassland cover and greater malaria prevalence in high intensity settings (prevalence odds ratio (POR): 1.10, 95% UI: 1.00, 1.21), and between greater forest cover and reduced malaria prevalence in low transmission areas (POR: 0.74, 95% UI: 0.51, 1.03), however the uncertainty intervals of both estimates included the null.

CONCLUSIONS

The intensity of malaria transmission appears to modify relationships between land cover and malaria prevalence among school-aged children in Tanzania. In particular, greater cropland cover was positively associated with increased malaria prevalence in areas with low transmission intensity and presents an actionable target for environmental vector control interventions to complement current malaria control activities. As areas are nearing malaria elimination, it is important to re-evaluate environmental risk factors and employ appropriate interventions to effectively address low-level malaria transmission.

Development and optimizing a simple and cost-effective medium for in vitro culture of Plasmodium berghei-ANKA strain with conserving its infectivity in BALB/c mice

OBJECTIVES

The current culture system for P. berghei still requires modifications in consistency and long-term maintenance of parasites considering their pathogenicity in culture media. Therefore, this study designed to further improvement of culture conditions and designing a cost-effective culture medium with minimum changes in pathogenicity for in vitro culture of P. berghei.

RESULTS

Results indicated that the rate of parasitaemia in our modified method remained statistically stable between days one to seven (P = 0.07). The current modified cultivation method was more efficient in maintaining of parasites for further days. Furthermore, in current method the stability of parasitaemia rate during day1 to day7 was in better rate compared to that in Ronan Jambou et al. and the differences between two methods were statistically significant (P = 0.001). The virulence of cultivated parasites in our modified method remained similar to frozen stock parasites as positive control group. No significant differences were seen in survival time between two groups of mice those were infected with either cultivated parasites or stock freeze parasites (P = 0.39) with the mean survival time of 20.83 ± 3.84 and 19.66 ± 1.21 days, respectively. Herein, we achieved a simple, cost-effective and applicable technique for culture of P. berghei.

Situation of insecticide resistance in malaria vectors in the World Health Organization of Eastern Mediterranean region 1990-2020

Malaria is the most important mosquito-borne disease, which is transmitted by Anopheles species. According to the recent report of World Health Organization, there were an estimated 229 million malaria cases in 2019 in 87 malaria endemic countries. There are several vector control method specially using pesticides. The aim of this study was to collect all the data about insecticide resistant of malaria vectors in the Eastern Mediterranean region countries. In this study, all the published papers related to insecticide resistance of malaria vectors in the region were collected and resistant status of vectors in the countries was mapped. Resistance to different insecticide classes such as pyrethroids, organophosphate, organochlorine and carbamates were evaluated using World Health Organization guidelines. Results showed a wide variety of susceptibility/resistance status to these chemicals according to the location, historical context of pesticide used, genetic background of vectors, age and abdominal conditions of adults may play a role in the susceptibility status of these species to different insecticides. The results of this study is providing a guideline for countries to manage their vector control activities against insecticide resistance of malaria vectors and provide novel approaches such as male sterility, using Wolbachia, using new insecticide with new mode of action.

Plasmodium falciparum parasite prevalence in East Africa: Updating data for malaria stratification

The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6-36.9) in Kenya, 10.6% (3.4-39.2) in mainland Tanzania, and 9.5% (4.0-48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (<1%) were inhabited by approximately 46.2 million people across the sub-region, or 52.2%, 26.7% and 10.4% of Kenya, mainland Tanzania and Uganda populations, respectively. In conclusion, parasite prevalence represents one of several data metrics for disease stratification at national and sub-national levels. To increase the use of this metric for decision making, there is a need to integrate other data layers on mortality related to malaria, malaria vector composition, insecticide resistance and bionomic, malaria care-seeking behaviour and current levels of unmet need of malaria interventions.

Seasonality of confirmed malaria cases from 2008 to 2017 in Togo: a time series analysis by health district and target group

Background

This study aimed to assess the seasonality of confirmed malaria cases in Togo and to provide new indicators of malaria seasonality to the National Malaria Control Programme (NMCP).

Methods

Aggregated data of confirmed malaria cases were collected monthly from 2008 to 2017 by the Togo’s NMCP and stratified by health district and according to three target groups: children < 5 years old, children ≥ 5 years old and adults, and pregnant women. Time series analysis was carried out for each target group and health district. Seasonal decomposition was used to assess the seasonality of confirmed malaria cases. Maximum and minimum seasonal indices, their corresponding months, and the ratio of maximum/minimum seasonal indices reflecting the importance of malaria transmission, were provided by health district and target group.

Results

From 2008 to 2017, 7,951,757 malaria cases were reported in Togo. Children < 5 years old, children ≥ 5 years old and adults, and pregnant women represented 37.1%, 57.7% and 5.2% of the confirmed malaria cases, respectively. The maximum seasonal indices were observed during or shortly after a rainy season and the minimum seasonal indices during the dry season between January and April in particular. In children < 5 years old, the ratio of maximum/minimum seasonal indices was higher in the north, suggesting a higher seasonal malaria transmission, than in the south of Togo. This is also observed in the other two groups but to a lesser extent.

Conclusions

This study contributes to a better understanding of malaria seasonality in Togo. The indicators of malaria seasonality could allow for more accurate forecasting in malaria interventions and supply planning throughout the year.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06893-z.

Spatial and spatio-temporal methods for mapping malaria risk: a systematic review

Background

Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA).

Methods

A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion.

Results

One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7–16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach.

Conclusions

Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology.

Pharmacokinetics and pharmacodynamics of azithromycin in severe malaria bacterial co-infection in African children (TABS-PKPD): a protocol for a Phase II randomised controlled trial

Background: African children with severe malaria are susceptible to Gram-negative bacterial co-infection, largely non-typhoidal Salmonellae, leading to a substantially higher rates of in-hospital and post-discharge mortality than those without bacteraemia. Current evidence for treating co-infection is lacking, and there is no consensus on the dosage or length of treatment required. We therefore aimed to establish the appropriate dose of oral dispersible azithromycin as an antimicrobial treatment for children with severe malaria and to investigate whether antibiotics can be targeted to those at greatest risk of bacterial co-infection using clinical criteria alone or in combination with rapid diagnostic biomarker tests. Methods: A Phase I/II open-label trial comparing three doses of azithromycin: 10, 15 and 20 mg/kg spanning the lowest to highest mg/kg doses previously demonstrated to be equally effective as parenteral treatment for other salmonellae infection. Children with the highest risk of bacterial infection will receive five days of azithromycin and followed for 90 days. We will generate relevant pharmacokinetic data by sparse sampling during dosing intervals. We will use population pharmacokinetic modelling to determine the optimal azithromycin dose in severe malaria and investigate azithromycin exposure to change in C-reactive protein, a putative marker of sepsis at 72 hours, and microbiological cure (seven-day), alone and as a composite with seven-day survival. We will also evaluate whether a combination of clinical, point-of-care diagnostic tests, and/or biomarkers can accurately identify the sub-group of severe malaria with culture-proven bacteraemia by comparison with a control cohort of children hospitalized with severe malaria at low risk of bacterial co-infection. Discussion: We plan to study azithromycin because of its favourable microbiological spectrum, its inherent antimalarial and immunomodulatory properties and dosing and safety profile. This study will generate new data to inform the design and sample size for definitive Phase III trial evaluation. Registration: ISRCTN49726849 (27th October 2017).

The impact of child health interventions and risk factors on child survival in Kenya, 1993-2014: a Bayesian spatio-temporal analysis with counterfactual scenarios

BACKGROUND

During the millennium development goals period, reduction in under-five mortality (U5M) and increases in child health intervention coverage were characterised by sub-national disparities and inequities across Kenya. The contribution of changing risk factors and intervention coverage on the sub-national changes in U5M remains poorly defined.

METHODS

Sub-national county-level data on U5M and 43 factors known to be associated with U5M spanning 1993 and 2014 were assembled. Using a Bayesian ecological mixed-effects regression model, the relationships between U5M and significant intervention and infection risk ecological factors were quantified across 47 sub-national counties. The coefficients generated were used within a counterfactual framework to estimate U5M and under-five deaths averted (U5-DA) for every county and year (1993-2014) associated with changes in the coverage of interventions and disease infection prevalence relative to 1993.

RESULTS

Nationally, the stagnation and increase in U5M in the 1990s were associated with rising human immunodeficiency virus (HIV) prevalence and reduced maternal autonomy while improvements after 2006 were associated with a decline in the prevalence of HIV and malaria, increase in access to better sanitation, fever treatment-seeking rates and maternal autonomy. Reduced stunting and increased coverage of early breastfeeding and institutional deliveries were associated with a smaller number of U5-DA compared to other factors while a reduction in high parity and fully immunised children were associated with under-five lives lost. Most of the U5-DA occurred after 2006 and varied spatially across counties. The highest number of U5-DA was recorded in western and coastal Kenya while northern Kenya recorded a lower number of U5-DA than western. Central Kenya had the lowest U5-DA. The deaths averted across the different regions were associated with a unique set of factors.

CONCLUSION

Contributions of interventions and risk factors to changing U5M vary sub-nationally. This has important implications for targeting future interventions within decentralised health systems such as those operated in Kenya. Targeting specific factors where U5M has been high and intervention coverage poor would lead to the highest likelihood of sub-national attainment of sustainable development goal (SDG) 3.2 on U5M in Kenya.

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.

Competing interests, clashing ideas and institutionalizing influence: insights into the political economy of malaria control from seven African countries

This article explores how malaria control in sub-Saharan Africa is shaped in important ways by political and economic considerations within the contexts of aid-recipient nations and the global health community. Malaria control is often assumed to be a technically driven exercise: the remit of public health experts and epidemiologists who utilize available data to select the most effective package of activities given available resources. Yet research conducted with national and international stakeholders shows how the realities of malaria control decision-making are often more nuanced. Hegemonic ideas and interests of global actors, as well as the national and global institutional arrangements through which malaria control is funded and implemented, can all influence how national actors respond to malaria. Results from qualitative interviews in seven malaria-endemic countries indicate that malaria decision-making is constrained or directed by multiple competing objectives, including a need to balance overarching global goals with local realities, as well as a need for National Malaria Control Programmes to manage and coordinate a range of non-state stakeholders who may divide up regions and tasks within countries. Finally, beyond the influence that political and economic concerns have over programmatic decisions and action, our analysis further finds that malaria control efforts have institutionalized systems, structures and processes that may have implications for local capacity development.

Chimpanzees balance resources and risk in an anthropogenic landscape of fear

Human-wildlife coexistence is possible when animals can meet their ecological requirements while managing human-induced risks. Understanding how wildlife balance these trade-offs in anthropogenic environments is crucial to develop effective strategies to reduce risks of negative interactions, including bi-directional aggression and disease transmission. For the first time, we use a landscape of fear framework with Bayesian spatiotemporal modelling to investigate anthropogenic risk-mitigation and optimal foraging trade-offs in Critically Endangered western chimpanzees (Pan troglodytes verus). Using 12 months of camera trap data (21 camera traps, 6722 camera trap days) and phenology on wild and cultivated plant species collected at Caiquene–Cadique, Cantanhez National Park (Guinea-Bissau), we show that humans and chimpanzees broadly overlapped in their use of forest and anthropogenic parts of the habitat including villages and cultivated areas. The spatiotemporal model showed that chimpanzee use of space was predicted by the availability of naturalised oil-palm fruit. Chimpanzees used areas away from villages and agriculture more intensively, but optimised their foraging strategies by increasing their use of village areas with cultivated fruits when wild fruits were scarce. Our modelling approach generates fine-resolution space–time output maps, which can be scaled-up to identify human-wildlife interaction hotspots at the landscape level, informing coexistence strategy.

Malaria in migrant agricultural workers in western Ethiopia: entomological assessment of malaria transmission risk

BACKGROUND

Ethiopia has made great strides in malaria control over the last two decades. However, this progress has not been uniform and one concern has been reported high rates of malaria transmission in large agricultural development areas in western Ethiopia. Improved vector control is one way this transmission might be addressed, but little is known about malaria vectors in this part of the country.

METHODS

To better understand the vector species involved in malaria transmission and their behaviour, human landing collections were conducted in Dangur woreda, Benishangul-Gumuz, between July and December 2017. This period encompasses the months with the highest rain and the peak mosquito population. Mosquitoes were identified to species and tested for the presence of Plasmodium sporozoites.

RESULTS

The predominant species of the Anopheles collected was Anopheles arabiensis (1,733; i.e. 61.3 % of the entire Anopheles), which was also the only species identified with sporozoites (Plasmodium falciparum and Plasmodium vivax). Anopheles arabiensis was collected as early in the evening as 18:00 h-19:00 h, and host-seeking continued until 5:00 h-6:00 h. Nearly equal numbers were collected indoors and outdoors. The calculated entomological inoculation rate for An. arabiensis for the study period was 1.41 infectious bites per month. More An. arabiensis were collected inside and outside worker's shelters than in fields where workers were working at night.

CONCLUSIONS

Anopheles arabiensis is likely to be the primary vector of malaria in the agricultural development areas studied. High rates of human biting took place inside and outdoor near workers' residential housing. Improved and targeted vector control in this area might considerably reduce malaria transmission.

Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of local climate zones (LCZs) for modeling malaria prevalence rate (Pf PR_2-10) and studying malaria prevalence in urban settings across nine sub-Saharan African cities. Using a random forest classification algorithm over a set of 365 malaria surveys we: (i) identify a suitable set of covariates derived from open-source earth observations; and (ii) depict the best buffer size at which to aggregate them for modeling Pf PR_2-10. Our results demonstrate that geographical models can learn from LCZ over a set of cities and be transferred over a city of choice that has few or no malaria surveys. In particular, we find that urban areas systematically have lower Pf PR_2-10 (5%-30%) than rural areas (15%-40%). The Pf PR_2-10 urban-to-rural gradient is dependent on the climatic environment in which the city is located. Further, LCZs show that more open urban environments located close to wetlands have higher Pf PR_2-10. Informal settlements-represented by the LCZ 7 (lightweight lowrise)-have higher malaria prevalence than other densely built-up residential areas with a mean prevalence of 11.11%. Overall, we suggest the applicability of LCZs for more exploratory modeling in urban malaria studies.

Spatial and genetic clustering of Plasmodium falciparum and Plasmodium vivax infections in a low-transmission area of Ethiopia

The distribution of malaria infections is heterogeneous in space and time, especially in low transmission settings. Understanding this clustering may allow identification and targeting of pockets of transmission. In Adama district, Ethiopia, Plasmodium falciparum and P. vivax malaria patients and controls were examined, together with household members and immediate neighbors. Rapid diagnostic test and quantitative PCR (qPCR) were used for the detection of infections that were genetically characterized by a panel of microsatellite loci for P. falciparum (26) and P. vivax (11), respectively. Individuals living in households of clinical P. falciparum patients were more likely to have qPCR detected P. falciparum infections (22.0%, 9/41) compared to individuals in control households (8.7%, 37/426; odds ratio, 2.9; 95% confidence interval, 1.3–6.4; P = .007). Genetically related P. falciparum, but not P. vivax infections showed strong clustering within households. Genotyping revealed a marked temporal cluster of P. falciparum infections, almost exclusively comprised of clinical cases. These findings uncover previously unappreciated transmission dynamics and support a rational approach to reactive case detection strategies for P. falciparum in Ethiopia.

Sero-epidemiological evaluation of malaria transmission in The Gambia before and after mass drug administration

BACKGROUND

As The Gambia aims to achieve malaria elimination by 2030, serological assays are a useful surveillance tool to monitor trends in malaria incidence and evaluate community-based interventions.

METHODS

Within a mass drug administration (MDA) study in The Gambia, where reduced malaria infection and clinical disease were observed after the intervention, a serological sub-study was conducted in four study villages. Spatio-temporal variation in transmission was measured with a panel of recombinant Pf antigens on a multiplexed bead-based assay. Village-level antibody levels were quantified as under-15 sero-prevalence, sero-conversion rates, and age-adjusted antibody acquisition rates. Antibody levels prior to MDA were assessed for association with persistent malaria infection after community chemoprophylaxis.

RESULTS

Seasonal changes in antibodies to Etramp5.Ag1 were observed in children under 15 years in two transmission settings-the West Coast and Upper River Regions (4.32% and 31.30% Pf prevalence, respectively). At the end of the malaria season, short-lived antibody responses to Etramp5.Ag1, GEXP18, HSP40.Ag1, EBA175 RIII-V, and Rh2.2030 were lower amongst 1-15 year olds in the West Coast compared to the Upper River, reflecting known differences in transmission. Prior to MDA, individuals in the top 50th percentile of antibody levels had two-fold higher odds of clinical malaria during the transmission season, consistent with previous findings from the Malaria Transmission Dynamics Study, where individuals infected before the implementation of MDA had two-fold higher odds of re-infection post-MDA.

CONCLUSIONS

Serological markers can serve dual functions as indicators of malaria exposure and incidence. By monitoring age-specific sero-prevalence, the magnitude of age-stratified antibody levels, or identifying groups of individuals with above-average antibody responses, these antigens have the potential to complement conventional malaria surveillance tools. Further studies, particularly cluster randomised trials, can help establish standardised serological protocols to reliably measure transmission across endemic settings.

Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicated Plasmodium falciparum malaria 1991-2019

BACKGROUND

Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use; its influence on malaria burden varies through space and time.

METHODS

This study uses data from 232 efficacy trials comprised of 86,776 infected individuals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries.

RESULTS

The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3-75.8), 70.1% (43.6-76.0) and 71.8% (46.9-76.4) for the 1991-2000, 2006-2010, and 2016-2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9-74.9) for 1991-2000 and 55.5% (27.1-73.4) for 2011-2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials.

CONCLUSIONS

This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries' treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.

Are Individuals Willing to Pay for Community-Based Eco-Friendly Malaria Vector Control Strategies? A Case of Mosquito Larviciding Using Plant-Based Biopesticides in Kenya

This study was carried out to assess individuals’ willingness to pay (WTP) for UZIMAX, a novel plant-based biopesticide developed for malaria vector control. The biopesticide is estimated to kill up to 100% of Anopheles larvae within 48 h of application and poses no risks to human health and the environment. However, scaling-up of its adoption requires clear evidence of its acceptance by individuals in malaria-prone areas. We conducted Becker-DeGroot-Marschak (BDM) revealed preference auctions with 204 participants to determine their willingness to pay (WTP) for community-based application of the biopesticide to control malaria vectors. Nearly all participants were willing to pay at the lowest bid price of the biopesticide, and the majority of them expressed great interest in pooling resources to facilitate biopesticide application. Household per capita income and building capacity of households through training significantly increased WTP. These findings imply high adoption potential of the technology and the need to devise inclusive policy tools, especially those that enhance collective action, resource mobilization and capacity building to empower both men and women and stimulate investment in eco-friendly technologies for malaria prevention. Financial and labor resource mechanisms managed by the community could potentially spur adoption of the biopesticides, and in turn, generate health, environmental and economic benefits to households in malaria-prone communities.

Geospatial estimation of reproductive, maternal, newborn and child health indicators: a systematic review of methodological aspects of studies based on household surveys

BACKGROUND

Geospatial approaches are increasingly used to produce fine spatial scale estimates of reproductive, maternal, newborn and child health (RMNCH) indicators in low- and middle-income countries (LMICs). This study aims to describe important methodological aspects and specificities of geospatial approaches applied to RMNCH coverage and impact outcomes and enable non-specialist readers to critically evaluate and interpret these studies.

METHODS

Two independent searches were carried out using Medline, Web of Science, Scopus, SCIELO and LILACS electronic databases. Studies based on survey data using geospatial approaches on RMNCH in LMICs were considered eligible. Studies whose outcomes were not measures of occurrence were excluded.

RESULTS

We identified 82 studies focused on over 30 different RMNCH outcomes. Bayesian hierarchical models were the predominant modeling approach found in 62 studies. 5 × 5 km estimates were the most common resolution and the main source of information was Demographic and Health Surveys. Model validation was under reported, with the out-of-sample method being reported in only 56% of the studies and 13% of the studies did not present a single validation metric. Uncertainty assessment and reporting lacked standardization, and more than a quarter of the studies failed to report any uncertainty measure.

CONCLUSIONS

The field of geospatial estimation focused on RMNCH outcomes is clearly expanding. However, despite the adoption of a standardized conceptual modeling framework for generating finer spatial scale estimates, methodological aspects such as model validation and uncertainty demand further attention as they are both essential in assisting the reader to evaluate the estimates that are being presented.

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BACKGROUND

The rapid and often uncontrolled rural-urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa's population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam.

METHODS

Openly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2-10 years (PfPR2-10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2-10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population.

RESULTS

The results suggest that the spatial distribution of PfPR2-10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2-10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values.

CONCLUSIONS

The outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.

Routine data for malaria morbidity estimation in Africa: challenges and prospects

BACKGROUND

The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented.

CONCLUSION

Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.

Epidemiological characteristics of imported malaria in Shandong Province, China, from 2012 to 2017

Shandong Province, China, has been implementing a malaria elimination program. In this study, we analyzed the epidemiological characteristics of malaria imported into Shandong Province between 2012 and 2017 to provide scientific data for the elimination of malaria. In this epidemiological study, we examined the status of malaria in 2012–2017 in Shandong Province, China. Data on all cases of malaria were collected from the online Infection Diseases Monitor Information System to describe and statistically analyze the sources of infection, species of parasite, populations affected, regional distributions, incidence, and temporal distributions of malaria. In total, 1053 cases of malaria were reported in 2012–2017, and all of them were imported. Plasmodium falciparum was the predominant species (77.6%) in Shandong Province; P. vivax malaria accounted for 10.9% of the total number of cases, P. ovale malaria for 2.9%, and P. malariae malaria for 8.2%. Most patients were male (96.8%), most were aged 21–50 years (87.2%), and migrant laborers (77.2%) and workers (6.6%) were at highest risk. The origin of the largest number of imported cases was Africa (93.4%), followed by Asia (5.9%) and Oceania (0.4%). Most cases of imported malaria occurred in June each year and 70% of cases were recorded in six cities during the period of 2012–2017. It is necessary to strengthen malaria surveillance among workers returning home from Africa and Southeast Asia, and to conduct timely blood tests to diagnose and treat imported infections.

Rapid shifts in the age-specific burden of malaria following successful control interventions in four regions of Uganda

Background

Malaria control using long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) has been associated with reduced transmission throughout Africa. However, the impact of transmission reduction on the age distribution of malaria cases remains unclear.

Methods

Over a 10-year period (January 2009 to July 2018), outpatient surveillance data from four health facilities in Uganda were used to estimate the impact of control interventions on temporal changes in the age distribution of malaria cases using multinomial regression. Interventions included mass distribution of LLINs at all sites and IRS at two sites.

Results

Overall, 896,550 patient visits were included in the study; 211,632 aged < 5 years, 171,166 aged 5–15 years and 513,752 > 15 years. Over time, the age distribution of patients not suspected of malaria and those malaria negative either declined or remained the same across all sites. In contrast, the age distribution of suspected and confirmed malaria cases increased across all four sites. In the two LLINs-only sites, the proportion of malaria cases in < 5 years decreased from 31 to 16% and 35 to 25%, respectively. In the two sites receiving LLINs plus IRS, these proportions decreased from 58 to 30% and 64 to 47%, respectively. Similarly, in the LLINs-only sites, the proportion of malaria cases > 15 years increased from 40 to 61% and 29 to 39%, respectively. In the sites receiving LLINs plus IRS, these proportions increased from 19 to 44% and 18 to 31%, respectively.

Conclusions

These findings demonstrate a shift in the burden of malaria from younger to older individuals following implementation of successful control interventions, which has important implications for malaria prevention, surveillance, case management and control strategies.

Creating mosquito-free outdoor spaces using transfluthrin-treated chairs and ribbons

BACKGROUND

Residents of malaria-endemic communities spend several hours outdoors performing different activities, e.g. cooking, story-telling or eating, thereby exposing themselves to potentially-infectious mosquitoes. This compromises effectiveness of indoor interventions, notably long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS). This study characterized common peri-domestic spaces in rural south-eastern Tanzania, and assessed protective efficacy against mosquitoes of hessian fabric mats and ribbons treated with the spatial repellent, transfluthrin, and fitted to chairs and outdoor kitchens, respectively.

METHODS

Two hundred households were surveyed, and their most-used peri-domestic spaces physically characterized. Protective efficacies of locally-made transfluthrin-emanating chairs and hessian ribbons were tested in outdoor environments of 28 households in dry and wet seasons, using volunteer-occupied exposure-free double net traps. CDC light traps were used to estimate host-seeking mosquito densities within open-structure outdoor kitchens. Field-collected Anopheles arabiensis and Anopheles funestus mosquitoes were exposed underneath the chairs to estimate 24 h-mortality. Finally, The World Health Organization insecticide susceptibility tests were conducted on wild-caught Anopheles from the villages.

RESULTS

Approximately half (52%) of houses had verandas. Aside from these verandas, most houses also had peri-domestic spaces where residents stayed most times (67% of houses with verandas and 94% of non-veranda houses). Two-thirds of these spaces were sited under trees, and only one third (34.4%) were built-up. The outdoor structures were usually makeshift kitchens having roofs and partial walls. Transfluthrin-treated chairs reduced outdoor-biting An. arabiensis densities by 70-85%, while transfluthrin-treated hessian ribbons fitted to the outdoor kitchens caused 77-81% reduction in the general peri-domestic area. Almost all the field-collected An. arabiensis (99.4%) and An. funestus (100%) exposed under transfluthrin-treated chairs died. The An. arabiensis were susceptible to non-pyrethroids (pirimiphos methyl and bendiocarb), but resistant to pyrethroids commonly used on LLINs (deltamethrin and permethrin).

CONCLUSION

Most houses had actively-used peri-domestic outdoor spaces where exposure to mosquitoes occurred. The transfluthrin-treated chairs and ribbons reduced outdoor-biting malaria vectors in these peri-domestic spaces, and also elicited significant mortality among pyrethroid-resistant field-caught malaria vectors. These two new prototype formats for transfluthrin emanators, if developed further, may constitute new options for complementing LLINs and IRS with outdoor protection against malaria and other mosquito-borne pathogens in areas where peri-domestic human activities are common.

Malaria

Malaria is a significant cause of morbidity and mortality throughout the world, and environmental changes are likely to increase its importance in the coming years. Diagnosing this disease is difficult and requires a high index of suspicion, especially in non-endemic countries. Critical care providers play a major role in treating severe malaria and its complications, which has management particularities that might not be readily apparent. Fluid resuscitation should be carefully tailored to avoid complications, and dysperfusion seems more related to degree of parasitemia than hypovolemia. Antimalarial agents are effective, but resistance is growing. Complications can be found in nearly every organ, including cerebral malaria, acute respiratory distress syndrome, and acute kidney injury. As such, a critical care unit is frequently required for organ support when they appear. Superimposed infections are not infrequent. Despite all of this, mortality is encouragingly low with a timely diagnosis and access to appropriate treatment.

Immune Responses to Gametocyte Antigens in a Malaria Endemic Population-The African falciparum Context: A Systematic Review and Meta-Analysis

Background: Malaria elimination remains a priority research agenda with the need for interventions that reduce and/or block malaria transmission from humans to mosquitoes. Transmission-blocking vaccines (TBVs) are in development, most of which target the transmission stage (i.e., gametocyte) antigens Pfs230 and Pfs48/45. For these interventions to be implemented, there is a need to understand the naturally acquired immunity to gametocytes. Several studies have measured the prevalence of immune responses to Pfs230 and Pfs48/45 in populations in malaria-endemic areas. Methods: We conducted a systematic review of studies carried out in African populations that measured the prevalence of immune responses to the gametocyte antigens Pfs230 and Pfs48/45. We assessed seroprevalence of antibody responses to the two antigens and investigated the effects of covariates such as age, transmission intensity/endemicity, season, and parasite prevalence on the prevalence of these antibody responses by meta-regression. Results: We identified 12 studies covering 23 sites for inclusion in the analysis. We found that the range of reported seroprevalence to Pfs230 and Pfs48/45 varied widely across studies, from 0 to 64% for Pfs48/45 and from 6 to 72% for Pfs230. We also found a modest association between increased age and increased seroprevalence to Pfs230: adults were associated with higher seroprevalence estimates in comparison to children (β coefficient 0.21, 95% CI: 0.05-0.38, p = 0.042). Methodological factors were the most significant contributors to heterogeneity between studies which prevented calculation of pooled prevalence estimates. Conclusions: Naturally acquired sexual stage immunity, as detected by antibodies to Pfs230 and Pfs48/45, was present in most studies analyzed. Significant between-study heterogeneity was seen, and methodological factors were a major contributor to this, and prevented further analysis of epidemiological and biological factors. This demonstrates a need for standardized protocols for conducting and reporting seroepidemiological analyses.

Detection of malaria with light microscopy and Nested polymerase chain reaction (Nested PCR) methods in peripheral blood expansions and investigation of the genetic diversity of Plasmodium species by 18S rRNA gene in Southeast of Iran

BACKGROUND

Malaria is a public health concern that leads to about a million deaths worldwide every year. Malaria is caused by the genus Plasmodium, which includes P. falciparum, P. vivax, P. malariae, and P. ovale. Molecular phylogeny is essential to better recognition the evolution of the genus Plasmodium genus and detection of the relative degree of Plasmodium species in humans. The aim of this study was to detect malaria with Light Microscopy (LM) and Nested polymerase chain reaction (Nested PCR) methods in peripheral blood expansions and to investigate the genetic diversity of Plasmodium species by 18S rRNA gene in the southeast of Iran.

METHODS

A total of 97 blood smears were collected from patients suspected to malaria in a 6-year period in the southeast of Iran including Hormozgan, Kerman, and Sistan and Baluchestan provinces. Diagnosis of Plasmodium species on blood smears was performed using LM and Nested PCR methods. In addition, 16 Plasmodium-positive samples were chosen for the determination of genetic diversity.

RESULTS

Overall, 97 of 97 (100%) studied cases were positive by LM while 94 of 97 (96.8%) of them were detected as malaria by Nested PCR. Except for seven cases, Nested PCR confirmed the LM results. These samples involved two P. vivax and five P. falciparum in the LM method. Meanwhile, the Nested PCR was detected in all of the cases as a mixed infection with P. vivax and P. falciparum. The results of the phylogenetic analysis revealed two main clades and five different subclades. About 87.5% of the isolates were located in clade I and contained P. vivax. In addition, 12.5% of the studied isolates involved P. falciparum that was in clade II.

CONCLUSION

According to our results, Nested PCR method had higher sensitivity than LM and is suggested as a good approach for malaria detection. Consideration the wide diversity of tested isolates and the importance of vaccine development, which is affected by this diversity, further studies are needed in this regard.

Plasmodium Genomics and Genetics: New Insights into Malaria Pathogenesis, Drug Resistance, Epidemiology, and Evolution

Protozoan Plasmodium parasites are the causative agents of malaria, a deadly disease that continues to afflict hundreds of millions of people every year. Infections with malaria parasites can be asymptomatic, with mild or severe symptoms, or fatal, depending on many factors such as parasite virulence and host immune status. Malaria can be treated with various drugs, with artemisinin-based combination therapies (ACTs) being the first-line choice. Recent advances in genetics and genomics of malaria parasites have contributed greatly to our understanding of parasite population dynamics, transmission, drug responses, and pathogenesis. However, knowledge gaps in parasite biology and host-parasite interactions still remain. Parasites resistant to multiple antimalarial drugs have emerged, while advanced clinical trials have shown partial efficacy for one available vaccine. Here we discuss genetic and genomic studies of Plasmodium biology, host-parasite interactions, population structures, mosquito infectivity, antigenic variation, and targets for treatment and immunization. Knowledge from these studies will advance our understanding of malaria pathogenesis, epidemiology, and evolution and will support work to discover and develop new medicines and vaccines.

Connected diagnostics: linking digital rapid diagnostic tests and mobile health wallets to diagnose and treat brucellosis in Samburu, Kenya

BACKGROUND

Despite WHO guidelines for testing all suspected cases of malaria before initiating treatment, presumptive malaria treatment remains common practice among some clinicians and in certain low-resource settings the capacity for microscopic testing is limited. This can lead to misdiagnosis, resulting in increased morbidity due to lack of treatment for undetected conditions, increased healthcare costs, and potential for drug resistance. This is particularly an issue as multiple conditions share the similar etiologies to malaria, including brucellosis, a rare, under-detected zoonosis. Linking rapid diagnostic tests (RDTs) and digital test readers for the detection of febrile illnesses can mitigate this risk and improve case management of febrile illness.

METHODS

This technical advance study examines Connected Diagnostics, an approach that combines the use of point-of-care RDTs for malaria and brucellosis, digitally interpreted by a rapid diagnostic test reader (Deki Reader) and connected to mobile payment mechanisms to facilitate the diagnosis and treatment of febrile illness in nomadic populations in Samburu County, Kenya. Consenting febrile patients were tested with RDTs and patient diagnosis and risk information were uploaded to a cloud database via the Deki Reader. Patients with positive diagnoses were provided digital vouchers for transportation to the clinic and treatment via their health wallet on their mobile phones.

RESULTS

In total, 288 patients were tested during outreach visits, with 9% testing positive for brucellosis and 0.6% testing positive for malaria. All patients, regardless of diagnosis were provided with a mobile health wallet on their cellular phones to facilitate their transport to the clinic, and for patients testing positive for brucellosis or malaria, the wallet funded their treatment. The use of the Deki Reader in addition to quality diagnostics at point of care also facilitated geographic mapping of patient diagnoses in relation to key risk areas for brucellosis transmission.

CONCLUSIONS

This study demonstrates that the Connected Dx approach can be effective even when addressing a remote, nomadic population and a rare disease, indicating that this approach to diagnosing, treatment, and payment for healthcare costs is feasible and can be scaled to address more prevalent diseases and conditions in more populous contexts.