Spatial and epidemiological drivers of Plasmodium falciparum malaria among adults in the Democratic Republic of the Congo

Malaria infection among adults residing in a highly endemic region from the Democratic Republic of the Congo

BACKGROUND

Adults infected with Plasmodium spp. in endemic areas need to be re-evaluated in light of global malaria elimination goals. They potentially undermine malaria interventions but remain an overlooked aspect of public health strategies.

METHODS

This study aimed to estimate the prevalence of Plasmodium spp. infections, to identify underlying parasite species, and to assess predicting factors among adults residing in an endemic area from the Democratic Republic of Congo (DRC). A community-based cross-sectional survey in subjects aged 18 years and above was therefore carried out. Study participants were interviewed using a standard questionnaire and tested for Plasmodium spp. using a rapid diagnostic test and a nested polymerase chain reaction assay. Logistic regression models were fitted to assess the effect of potential predictive factors for infections with different Plasmodium spp.

RESULTS

Overall, 420 adults with an estimated prevalence of Plasmodium spp. infections of 60.2% [95% CI 55.5; 64.8] were included. Non-falciparum species infected 26.2% [95% CI 22.2; 30.5] of the study population. Among infected participants, three parasite species were identified, including Plasmodium falciparum (88.5%), Plasmodium malariae (39.9%), and Plasmodium ovale (7.5%) but no Plasmodium vivax. Mixed species accounted for 42.3% of infections while single-species infections predominated with P. falciparum (56.5%) among infected participants. All infected participants were asymptomatic at the time of the survey. Adults belonging to the "most economically disadvantaged" households had increased risks of infections with any Plasmodium spp. (adjusted odds ratio, aOR = 2.87 [95% CI 1.66, 20.07]; p < 0.001), compared to those from the "less economically disadvantaged" households. Conversely, each 1 year increase in age reduced the risk of infections with any Plasmodium spp. (aOR = 0.99 [95% CI 0.97, 0.99]; p = 0.048). Specifically for non-falciparum spp., males had increased risks of infection than females (aOR = 1.83 [95% CI 1.13, 2.96]; p = 0.014).

CONCLUSION

Adults infected with malaria constitute a potentially important latent reservoir for the transmission of the disease in the study setting. They should specifically be taken into account in public health measures and translational research.

Modeling clinical malaria episodes in different ecological settings in Mali, 2018-2022

Objectives

Following the scaling-up of malaria control strategies in Mali, understanding the changes in age-specific prevalence of infection and risk factors associated with remains necessary to determine new priorities to progress toward disease elimination. This study aimed to estimate the risk of clinical malaria using longitudinal data across three different transmission settings in Mali.

Methods

Cohort-based longitudinal studies were performed from April 2018 to December 2022. Incidence of malaria was measured through community health center-based passive case detection. Generalized estimation equation model was used to assess risk factors for clinical malaria.

Results

A total of 21,453 clinical presentations were reported from 4500 participants, mainly from July to November. Data shows a significant association between malaria episodes, sex, age group, season, and year. Women had lower risk, the risk of clinical episode increased with age up to 14 years then declined, and in both sites, the dry-season risk of clinical episode was significantly lower compared to the rainy season.

Conclusion

Determining factors associated with the occurrence of clinical malaria across different ecological settings across the country could help in the development of new strategies aiming to accelerate malaria elimination in an area where malaria transmission remains intense.

Urbanicity and child health in 26 sub-Saharan African countries: Settlement type and its association with mortality and morbidity

Urbanization and changing settlement patterns have affected health environments in African countries. A profound understanding of the intricate association between urbanicity and health is imperative for formulating effective interventions. This study aims to classify settlement types based on urbanicity and assess their effects on child health in 26 African countries, utilizing data from the Demographic and Health Survey and the Global Human Settlements Layer. The advanced settlement classification incorporates a multidimensional urbanicity scale and globally standardized urban extents, along with identifying urban slums. This approach derives six distinct settlement types: urban center, urban cluster, deprived urban settlement, rural town, rural cluster, and rural village. A multilevel logistic regression model examines the relationship between settlement types and health outcomes, encompassing mortality, fever, anemia, diarrhea, and cough in children under five. The analysis reveals that children living in rural villages and deprived urban settlements face a high burden of adverse health conditions. However, the size and direction of urbanicity's effects vary depending on the specific outcome. These findings highlight the significance of tailored interventions acknowledging health environments within each settlement to promote health equity.

Association between domesticated animal ownership and Plasmodium falciparum parasite prevalence in the Democratic Republic of the Congo: a national cross-sectional study

BACKGROUND

Domesticated animal ownership is an understudied aspect of the human environment that influences mosquito biting behaviour and malaria transmission, and is a key part of national economies and livelihoods in malaria-endemic regions. In this study, we aimed to understand differences in Plasmodium falciparum prevalence by ownership status of common domesticated animals in DR Congo, where 12% of the world's malaria cases occur and anthropophilic Anopheles gambiae vectors predominate.

METHODS

In this cross-sectional study, we used survey data from individuals aged 15-59 years in the most recent (2013-14) DR Congo Demographic and Health Survey and previously performed Plasmodium quantitative real-time PCR (qPCR) to estimate P falciparum prevalence differences by household ownership of cattle; chickens; donkeys, horses, or mules; ducks; goats; sheep; and pigs. We used directed acyclic graphs to consider confounding by age, gender, wealth, modern housing, treated bednet use, agricultural land ownership, province, and rural location.

FINDINGS

Of 17 701 participants who had qPCR results and covariate data, 8917 (50·4%) of whom owned a domesticated animal, we observed large differences in malaria prevalence across types of animals owned in both crude and adjusted models. Household chicken ownership was associated with 3·9 (95% CI 0·6 to 7·1) more P falciparum infections per 100 people, whereas cattle ownership was associated with 9·6 (-15·8 to -3·5) fewer P falciparum infections per 100 people, even after accounting for bednet use, wealth, and housing structure.

INTERPRETATION

Our finding of a protective association conferred by cattle ownership suggests that zooprophylaxis interventions might have a role in DR Congo, possibly by drawing An gambiae feeding away from humans. Studies of animal husbandry practices and associated mosquito behaviours could reveal opportunities for new malaria interventions.

FUNDING

The National Institutes of Health and the Bill & Melinda Gates Foundation.

TRANSLATIONS

For the French and Lingala translations of the abstract see Supplementary Materials section.

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.

The impact of the private sector co-payment mechanism (PSCM) on the private market for ACT in Nigeria: results of the 2018 cross-sectional outlet and household market surveys

Background

The private sector plays a large role in malaria treatment provision in Nigeria. To improve access to, and affordability of, quality-assured artemisinin-based combination therapy (QA-ACT) within this sector, the Affordable Medicines Facility-Malaria began operations in 2010 and transitioned to a private sector co-payment mechanism (PSCM) until 2017. To assess the impact of the scheme on the ACT market, cross-sectional household and outlet surveys were conducted in 2018 to coincide with the final stockages of ACT medicines procured under the PSCM.

Methods

An outlet survey was conducted targeting private pharmacies and Proprietary and Patent Medicine Vendors (PPMVs) across different regions of Nigeria to assess supply-side market factors related to availability and cost of anti-malarials, including artemisinin-based combinations subsidised under the PSCM (called green leaf ACT on account of their green leaf logo) and those not subsidised (non-green leaf ACT). A concurrent household survey was conducted to determine demand-side factors related to treatment-seeking practices, ACT brand preference and purchase decision. Data were compared with previous ACTWatch surveys to consider change over time.

Results

Availability of artemisinin-based combinations increased significantly over the PSCM period and was almost universal by the time of the 2018 market survey. This increase was seen particularly among PPMVs. While the cost of green leaf ACT remained relatively stable over time, the cost of non-green leaf ACT reduced significantly so that by 2018 they had equivalent affordability. Unsubsidised brands were also available in different formulations and dosages, with double-strength artemisinin-based combination reported as the most frequently purchased dosage type, and child artemisinin-based combinations popular in suspension and dispersible forms (forms not subsidised by the PSCM).

Conclusions

The PSCM had a clear impact on increasing not only the reach of subsidized QA brands, but also of non-subsidised brands. Increased market competition led to innovation from unsubsidised brands and large reductions in costs to make them competitive with subsidised brands. Concerns are drawn from the large market share that non-QA brands have managed to gain as well as the continued market share of oral artemisinin monotherapies. Continued monitoring of the market is recommended, along with improved local capacity for QA-certification and monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-04039-9.

Impact of extractive industries on malaria prevalence in the Democratic Republic of the Congo: a population-based cross-sectional study

Extraction of natural resources through mining and logging activities provides revenue and employment across sub-Saharan Africa, a region with the highest burden of malaria globally. The extent to which mining and logging influence malaria transmission in Africa remains poorly understood. Here, we evaluate associations between mining, logging, and malaria in the high transmission setting of the Democratic Republic of the Congo using population-representative malaria survey results and geographic data for environmental features and mining and logging concessions. We find elevated malaria prevalence among individuals in rural areas exposed to mining; however, we also detect significant spatial confounding among locations. Upon correction, effect estimates for mining and logging shifted toward the null and we did not find sufficient evidence to detect an association with malaria. Our findings reveal a complex interplay between mining, logging, space, and malaria prevalence. While mining concessions alone may not drive the high prevalence, unobserved features of mining-exposed areas, such as human migration, changing vector populations, or parasite genetics, may instead be responsible.

Genetic surveillance for monitoring the impact of drug use on Plasmodium falciparum populations

The use of antimalarial drugs is an effective strategy in the fight against malaria. However, selection of drug resistant parasites is a constant threat to the continued use of this approach. Antimalarial drugs are used not only to treat infections but also as part of population-level strategies to reduce malaria transmission toward elimination. While there is strong evidence that the ongoing use of antimalarial drugs increases the risk of the emergence and spread of drug-resistant parasites, it is less clear how population-level use of drug-based interventions like seasonal malaria chemoprevention (SMC) or mass drug administration (MDA) may contribute to drug resistance or loss of drug efficacy. Critical to sustained use of drug-based strategies for reducing the burden of malaria is the surveillance of population-level signals related to transmission reduction and resistance selection. Here we focus on Plasmodium falciparum and discuss the genetic signatures of a parasite population that are correlated with changes in transmission and related to drug pressure and resistance as a result of drug use. We review the evidence for MDA and SMC contributing to malaria burden reduction and drug resistance selection and examine the use and impact of these interventions in Senegal. Throughout we consider best strategies for ongoing surveillance of both population and resistance signals in the context of different parasite population parameters. Finally, we propose a roadmap for ongoing surveillance during population-level drug-based interventions to reduce the global malaria burden.

The epidemiology of Plasmodium vivax among adults in the Democratic Republic of the Congo

Reports of P. vivax infections among Duffy-negative hosts have accumulated throughout sub-Saharan Africa. Despite this growing body of evidence, no nationally representative epidemiological surveys of P. vivax in sub-Saharan Africa have been performed. To overcome this gap in knowledge, we screened over 17,000 adults in the Democratic Republic of the Congo (DRC) for P. vivax using samples from the 2013-2014 Demographic Health Survey. Overall, we found a 2.97% (95% CI: 2.28%, 3.65%) prevalence of P. vivax infections across the DRC. Infections were associated with few risk-factors and demonstrated a relatively flat distribution of prevalence across space with focal regions of relatively higher prevalence in the north and northeast. Mitochondrial genomes suggested that DRC P. vivax were distinct from circulating non-human ape strains and an ancestral European P. vivax strain, and instead may be part of a separate contemporary clade. Our findings suggest P. vivax is diffusely spread across the DRC at a low prevalence, which may be associated with long-term carriage of low parasitemia, frequent relapses, or a general pool of infections with limited forward propagation.

The Burden of Malaria in the Democratic Republic of the Congo

Despite evidence that older children and adolescents bear the highest burden of malaria, large malaria surveys focus on younger children. We used polymerase chain reaction data from the 2013-2014 Demographic and Health Survey in the Democratic Republic of Congo (including children aged <5 years and adults aged ≥15 years) and a longitudinal study in Kinshasa Province (participants aged 6 months to 98 years) to estimate malaria prevalence across age strata. We fit linear models and estimated prevalences for each age category; adolescents aged 10-14 years had the highest prevalence. We estimate approximately 26 million polymerase chain reaction-detectable infections nationally. Adolescents and older children should be included in surveillance studies.

Impact of 1.5 oC and 2 oC global warming scenarios on malaria transmission in East Africa

Background: Malaria remains a global challenge with approximately 228 million cases and 405,000 malaria-related deaths reported in 2018 alone; 93% of which were in sub-Saharan Africa. Aware of the critical role than environmental factors play in malaria transmission, this study aimed at assessing the relationship between precipitation, temperature, and clinical malaria cases in East Africa and how the relationship may change under 1.5 ^oC and 2.0 ^oC global warming levels (hereinafter GWL1.5 and GWL2.0, respectively).

Methods: A correlation analysis was done to establish the current relationship between annual precipitation, mean temperature, and clinical malaria cases. Differences between annual precipitation and mean temperature value projections for periods 2008-2037 and 2023-2052 (corresponding to GWL1.5 and GWL2.0, respectively), relative to the control period (1977-2005), were computed to determine how malaria transmission may change under the two global warming scenarios.

Results: A predominantly positive/negative correlation between clinical malaria cases and temperature/precipitation was observed. Relative to the control period, no major significant changes in precipitation were shown in both warming scenarios. However, an increase in temperature of between 0.5 ^oC and 1.5 ^oC and 1.0 ^oC to 2.0 ^oC under GWL1.5 and GWL2.0, respectively, was recorded. Hence, more areas in East Africa are likely to be exposed to temperature thresholds favourable for increased malaria vector abundance and, hence, potentially intensify malaria transmission in the region.

Conclusions: GWL1.5 and GWL2.0 scenarios are likely to intensify malaria transmission in East Africa. Ongoing interventions should, therefore, be intensified to sustain the gains made towards malaria elimination in East Africa in a warming climate.

Impact of 1.5 oC and 2 oC global warming scenarios on malaria transmission in East Africa

Background: Malaria remains a global challenge with approximately 228 million cases and 405,000 malaria-related deaths reported in 2018 alone; 93% of which were in sub-Saharan Africa. Aware of the critical role than environmental factors play in malaria transmission, this study aimed at assessing the relationship between precipitation, temperature, and clinical malaria cases in East Africa and how the relationship may change under 1.5 oC and 2.0 oC global warming levels (hereinafter GWL1.5 and GWL2.0, respectively). Methods: A correlation analysis was done to establish the current relationship between annual precipitation, mean temperature, and clinical malaria cases. Differences between annual precipitation and mean temperature value projections for periods 2008-2037 and 2023-2052 (corresponding to GWL1.5 and GWL2.0, respectively), relative to the control period (1977-2005), were computed to determine how malaria transmission may change under the two global warming scenarios. Results: A predominantly positive/negative correlation between clinical malaria cases and temperature/precipitation was observed. Relative to the control period, no major significant changes in precipitation were shown in both warming scenarios. However, an increase in temperature of between 0.5 oC and 1.5 oC and 1.0 oC to 2.0 oC under GWL1.5 and GWL2.0, respectively, was recorded. Hence, more areas in East Africa are likely to be exposed to temperature thresholds favourable for increased malaria vector abundance and, hence, potentially intensify malaria transmission in the region. Conclusions: GWL1.5 and GWL2.0 scenarios are likely to intensify malaria transmission in East Africa. Ongoing interventions should, therefore, be intensified to sustain the gains made towards malaria elimination in East Africa in a warming climate.

Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.

Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.

Asymptomatic Plasmodium falciparum malaria prevalence among adolescents and adults in Malawi, 2015-2016

Malaria remains a significant cause of morbidity and mortality in Malawi, with an estimated 18–19% prevalence of Plasmodium falciparum in children 2–10 years in 2015–2016. While children report the highest rates of clinical disease, adults are thought to be an important reservoir to sustained transmission due to persistent asymptomatic infection. The 2015–2016 Malawi Demographic and Health Survey was a nationally representative household survey which collected dried blood spots from 15,125 asymptomatic individuals ages 15–54 between October 2015 and February 2016. We performed quantitative polymerase chain reaction on 7,393 samples, detecting an overall P. falciparum prevalence of 31.1% (SE = 1.1). Most infections (55.6%) had parasitemias ≤ 10 parasites/µL. While 66.2% of individuals lived in a household that owned a bed net, only 36.6% reported sleeping under a long-lasting insecticide-treated net (LLIN) the previous night. Protective factors included urbanicity, greater wealth, higher education, and lower environmental temperatures. Living in a household with a bed net (prevalence difference 0.02, 95% CI − 0.02 to 0.05) and sleeping under an LLIN (0.01; − 0.02 to 0.04) were not protective against infection. Our findings demonstrate a higher parasite prevalence in adults than published estimates among children. Understanding the prevalence and distribution of asymptomatic infection is essential for targeted interventions.

The Burden of Malaria in the Democratic Republic of the Congo

Despite evidence that older children and adolescents bear the highest burden of malaria, large malaria surveys focus on younger children. We used polymerase chain reaction data from the 2013-2014 Demographic and Health Survey in the Democratic Republic of Congo (including children aged <5 years and adults aged ≥15 years) and a longitudinal study in Kinshasa Province (participants aged 6 months to 98 years) to estimate malaria prevalence across age strata. We fit linear models and estimated prevalences for each age category; adolescents aged 10-14 years had the highest prevalence. We estimate approximately 26 million polymerase chain reaction-detectable infections nationally. Adolescents and older children should be included in surveillance studies.

Under the Radar: Epidemiology of Plasmodium ovale in the Democratic Republic of the Congo

BACKGROUND

Plasmodium ovale is an understudied malaria species prevalent throughout much of sub-Saharan Africa. Little is known about the distribution of ovale malaria and risk factors for infection in areas of high malaria endemicity.

METHODS

Using the 2013 Democratic Republic of the Congo (DRC) Demographic and Health Survey, we conducted a risk factor analysis for P. ovale infections. We evaluated geographic clustering of infections and speciated to P. ovale curtisi and P. ovale wallikeri through deep sequencing.

RESULTS

Of 18 149 adults tested, we detected 143 prevalent P. ovale infections (prevalence estimate 0.8%; 95% confidence interval [CI], .59%-.98%). Prevalence ratios (PR) for significant risk factors were: male sex PR = 2.12 (95% CI, 1.38-3.26), coprevalent P. falciparum PR = 3.52 (95% CI, 2.06-5.99), and rural residence PR = 2.19 (95% CI, 1.31-3.66). P. ovale was broadly distributed throughout the DRC; an elevated cluster of infections was detected in the south-central region. Speciation revealed P. ovale curtisi and P. ovale wallikeri circulating throughout the country.

CONCLUSIONS

P. ovale persists broadly in the DRC, a high malaria burden country. For successful elimination of all malaria species, P. ovale needs to be on the radar of malaria control programs.