A systematic review of changing malaria disease burden in sub-Saharan Africa since 2000: comparing model predictions and empirical observations

Predictors of insecticide-treated nets utilization among children under five years in refugee settlements in Uganda: analysis of the 2018-2019 Uganda Malaria Indicator Survey

BACKGROUND

Despite significant distribution of insecticide-treated net (ITNs) by the Government of Uganda to refugees, malaria is major cause of mortality and morbidity among children under five years in refugee settlements. This highlights the persistent challenges and complexities surrounding malaria control and prevention efforts in these settings. Studies that focus on the determinants of ITN utilization among children under five years in refugee settlements in Uganda are not available. Using the 2018-2019 Uganda's Malaria Indicator Survey (UMIS) data, analysis of the individual and household factors associated with utilization of ITN among children under five in refugee settlements of Uganda was conducted.

METHODS

This study focused on 589 children under five staying in refugee settlements located in Uganda. The extracted variables from the UMIS included social-economic factors associated with ITN utilization. Descriptive analysis was performed to generate summarized statistics, while inferential statistics by way of bivariate analysis were performed to assess the association between the outcome and the independent variables using the chi-square test, and multivariable logistic regression modelling to assess the magnitude of the associations after controlling for other covariates. All analyses considered the survey sampling design and sampling weights, and are conducted in Stata version 18.

RESULTS

The odds of children sleeping under ITN were higher if their mothers had secondary and higher education (8.1 times) as well as primary education (1.5 times). The odds of children sleeping under ITN reduced by 50% if their mothers were pregnant. Interestingly, the odds of children sleeping under ITN were 70% lower if their mothers knew that 'not sleeping in nets' caused malaria. Mothers who were exposed to malaria messages had lower odds of their children sleeping under ITNs.

CONCLUSIONS

The results highlight areas of intervention that can increase ITN use in refugee settlements of Uganda. Improving access to education for mothers, providing targeted health education on the importance of ITN, dispelling misconceptions about malaria transmission, facilitating the proper installation of ITNs among others, can all contribute to increased ITN utilization among children under five.

Spatial, temporal, and spatiotemporal cluster detection of malaria incidence in Southwest Ethiopia

Background

Malaria is a major global health hazard, particularly in developing countries such as Ethiopia, where it contributes to high morbidity and mortality rates. According to reports from the South Omo Zone Health Bureau, despite various interventions such as insecticide-treated bed nets and indoor residual spraying, the incidence of malaria has increased in recent years. Therefore, this study aimed to assess the spatial, temporal, and spatiotemporal variation in malaria incidence in the South Omo Zone, Southwest Ethiopia.

Methods

A retrospective study was conducted using 4 years of malaria data from the South Omo Zone District Health Information Software (DHIS). The incidence rate of malaria per 1,000 people was calculated using Microsoft Excel software. Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant spatial, temporal, and spatiotemporal malaria clusters. Graduated color maps depicting the incidence of malaria were generated using ArcGIS 10.7 software.

Results

Spatial clusters were identified in the districts of Dasenech (RR = 2.06, p < 0.0001), Hamer (RR = 1.90, p < 0.0001), Salamago (RR = 2.00, p < 0.0001), Bena Tsemay (RR = 1.71, p < 0.0001), Malie (RR = 1.50, p < 0.0001), Nyngatom (RR = 1.91, p < 0.0001) and North Ari (RR = 1.05, p < 0.0001) during the period from 08th July 2019 to 07th July 2023. A temporal cluster was identified as the risk period across all districts between 08th July 2022 and 07th July 2023 (RR = 1.59, p = 0.001). Spatiotemporal clusters were detected in Dasenech (RR = 2.26, p < 0.001) Salamago, (RR = 2.97, p < 0.001) Hamer (RR = 1.95, p < 0.001), Malie (RR = 2.03, p < 0.001), Bena Tsemay (RR = 1.80, p < 0.001), Nyngatom (RR = 2.65, p < 0.001), North Ari (RR = 1.50, p < 0.001), and Jinka town (RR = 1.19, p < 0.001).

Conclusion

Significant spatial, temporal, and spatiotemporal clusters in malaria incidence were identified in the South Omo Zone. To better understand the factors contributing to these high-risk areas, further research is needed to explore individual, household, geographical, and climatic factors. Targeted interventions based on these findings could help reduce malaria incidence and associated risks in the region.

Managing vector-borne diseases in a geoAI-enabled society. Malaria as an example

More than 17 % of all infectious diseases are caused by vector-borne diseases resulting in more than 1 billion cases and over 1 million deaths each year. Of these malaria continues to be a global burden in over eighty countries. As societies become more digitalised, the availability of geospatially enabled health and disease information will become more abundant. With this, the ability to assess health and disease risks in real-time will become a reality. The purpose of this study was to examine how geographic information, geospatial technologies and spatial data science are being used to reduce the burden of vector-borne diseases such as malaria and explore the opportunities that lie ahead with GeoAI and other geospatial technology advancements. Malaria is a dynamic and complex system and as such a range of data and approaches are needed to tackle different parts of the malaria cycle at different local and global scales. Geospatial technologies provide an integrated framework vital for monitoring, analysing and managing vector-borne diseases. GeoAI and technological advancements are useful for enhancing real-time assessments, accelerating the decision making process and spatial targeting of interventions. Training is needed to enhance the use of geospatial information for the management of vector-borne diseases.

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

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

Bayesian belief network modelling approach for predicting and ranking risk factors for malaria infections among children under 5 years in refugee settlements in Uganda

BACKGROUND

Malaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria's transmission complexity, control, and integrated modelling, with no available evidence on Uganda's refugee settlements. Using the 2018-2019 Uganda's Malaria Indicator Survey (UMIS) data, an alternative Bayesian belief network (BBN) modelling approach was used to analyse, predict, rank and illustrate the conceptual reasoning, and complex causal relationships among the risk factors for malaria infections among children under-five in refugee settlements of Uganda.

METHODS

In the UMIS, household level information was obtained using standardized questionnaires, and a total of 675 children under 5 years were tested for malaria. From the dataset, a casefile containing malaria test results, demographic, social-economic and environmental information was created. The casefile was divided into a training (80%, n = 540) and testing (20%, n = 135) datasets. The training dataset was used to develop the BBN model following well established guidelines. The testing dataset was used to evaluate model performance.

RESULTS

Model accuracy was 91.11% with an area under the receiver-operating characteristic curve of 0.95. The model's spherical payoff was 0.91, with the logarithmic, and quadratic losses of 0.36, and 0.16 respectively, indicating a strong predictive, and classification ability of the model. The probability of refugee children testing positive, and negative for malaria was 48.1% and 51.9% respectively. The top ranked malaria risk factors based on the sensitivity analysis included: (1) age of child; (2) roof materials (i.e., thatch roofs); (3) wall materials (i.e., poles with mud and thatch walls); (4) whether children sleep under insecticide-treated nets; 5) type of toilet facility used (i.e., no toilet facility, and pit latrines with slabs); (6) walk time distance to water sources (between 0 and 10 min); (7) drinking water sources (i.e., open water sources, and piped water on premises).

CONCLUSION

Ranking, rather than the statistical significance of the malaria risk factors, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted malaria interventions within the constraints of limited funding in the refugee settlements.

An Estimate Of The Return On Investment Of A Malaria Vaccine In 20 Sub-Saharan African Countries, 2021-30

Malaria is a leading global health problem that was responsible for an estimated 619,000 deaths worldwide in 2021. We modeled the return on investment (ROI) for the introduction and continuation of a four-dose malaria vaccine, RTS,S/AS01, from 2021 to 2030 in twenty sub-Saharan African countries supported by Gavi, the Vaccine Alliance. We used the Decade of Vaccine Economics benefits and costing outputs to calculate an ROI using health impact data modeled by the Swiss Tropical and Public Health Institute (hereafter "Swiss") and Imperial College London (hereafter "Imperial"). The Swiss estimates with a base vaccine price of US$7.00 resulted in an ROI of 0.42, and the Imperial impact estimates with the same base vaccine price resulted in an ROI of 2.30. Inclusion of the fifth seasonal dose for ten countries exhibiting high seasonal disease burden increased the Swiss ROI by 143 percent, to 1.02, and the Imperial ROI by 23.5 percent, to 2.84. To improve ROI, decision makers should continue to improve delivery platforms, decrease vaccine delivery costs, deliver the malaria vaccine in fewer doses, and provide access to vaccine resources.

Prevalence of malaria-helminth co-infections among children living in a setting of high coverage of standard interventions for malaria and helminths: Two population-based studies in Senegal

Background

Concurrent infections of Plasmodium falciparum with Soil Transmitted Helminths (STH) and Schistosoma spp are still a major public health problem among children living in Sub-Saharan Africa. We conducted two prospective studies among children living in urban and rural settings of Senegal, where control programmes for malaria, STH and schistosomiasis have been sustained, to determine the prevalence of malaria-helminth co-infection.

Methods

We enrolled 910 children aged 1-14 years from Saraya and Diourbel districts of Senegal in June and November 2021, respectively. We collected finger-prick blood samples from the children for malaria parasite detection using microscopy and PCR methods. Stool samples were also collected and Kato-Katz and PCR methods were used to detect STH and S. mansoni; and Merthiolate-iodine-formalin (MIF) test for other intestinal protozoans. Urine samples were analyzed using a filtration test, Point of Care Circulating Cathodic Antigens (POC-CCA) and PCR methods for detection of S. haematobium. Statistical analyses were performed to compare the continuous and categorical variables across the two study sites and age groups, as well as using the adjusted Odds ratios (aOR) to explore risk factors for malaria-helminth co-infections.

Results

The overall prevalence of polyparasitism with P. falciparum, STH, S. haematobium and S. mansoni among children in the two study sites was 2.2% (20/910) while prevalence of P. falciparum-S. haematobium co-infection was 1.1% (10/910); P. falciparum-S. mansoni 0.7% (6/910) and P. falciparum with any intestinal protozoan 2.4% (22/910). Co-infection was slightly higher among 5-14 year old children (17/629, 2.7%; 95% CI: 1.43-3.97) than 1-4 years (3/281, 1.1%; 95% CI: -0.12-2.32) and, in boys (13/567, 2.3%; 95% CI: 1.27-3.96) than girls (7/343, 2.1%; 95% CI: 0.52-3.48). Children aged 5-14 years (aOR = 3.37; 95% CI: 0.82-13.77, p = 0.09), who were boys (aOR = 1.44; 95% CI: 0.48-4.36, p = 0.51) and lived in Saraya (aOR = 1.27; 95% CI: 0.24-6.69, p = 0.77) had a higher risk of malaria-helminth co-infection than other age group, in girls and those who lived in Diourbel. Living in houses with spaces between the walls and roofs as well as frequent contacts with water during swimming were statistically significant risk factors for malaria-helminth co-infection.

Conclusions

The prevalence of malaria-helminth co-infection is low in two districts in Senegal, possibly due to sustained implementation of effective control measures for malaria and NTDs. These findings could help to develop and implement strategies that would lead to elimination of malaria and helminths in the study areas.

Malaria and Helminthic Co-Infection during Pregnancy in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

Malaria and helminthic co-infection during pregnancy causes fetomaternal haemorrhage and foetal growth retardation. This study determined the pooled burden of pregnancy malaria and helminthic co-infection in sub-Saharan Africa. CINAHL, EMBASE, Google Scholar, Scopus, PubMed, and Web of Science databases were used to retrieve data from the literature, without restricting language and publication year. The Joanna Briggs Institute's critical appraisal tool for prevalence studies was used for quality assessment. STATA Version 14.0 was used to conduct the meta-analysis. The I2 statistics and Egger's test were used to test heterogeneity and publication bias. The random-effects model was used to estimate the pooled prevalence at a 95% confidence interval (CI). The review protocol has been registered in PROSPERO, with the number CRD42019144812. In total, 24 studies (n = 14,087 participants) were identified in this study. The pooled analysis revealed that 20% of pregnant women were co-infected by malaria and helminths in sub-Saharan Africa. The pooled prevalence of malaria and helminths were 33% and 35%, respectively. The most prevalent helminths were Hookworm (48%), Ascaris lumbricoides (37%), and Trichuris trichiura (15%). Significantly higher malaria and helminthic co-infection during pregnancy were observed. Health systems in sub-Saharan Africa must implement home-grown innovative solutions to underpin context-specific policies for the early initiation of effective intermittent preventive therapy.

Controlled human malaria infection (CHMI) outcomes in Kenyan adults is associated with prior history of malaria exposure and anti-schizont antibody response

Background

Individuals living in endemic areas acquire immunity to malaria following repeated parasite exposure. We sought to assess the controlled human malaria infection (CHMI) model as a means of studying naturally acquired immunity in Kenyan adults with varying malaria exposure.

Methods

We analysed data from 142 Kenyan adults from three locations representing distinct areas of malaria endemicity (Ahero, Kilifi North and Kilifi South) enrolled in a CHMI study with Plasmodium falciparum sporozoites NF54 strain (Sanaria® PfSPZ Challenge). To identify the in vivo outcomes that most closely reflected naturally acquired immunity, parameters based on qPCR measurements were compared with anti-schizont antibody levels and residence as proxy markers of naturally acquired immunity.

Results

Time to endpoint correlated more closely with anti-schizont antibodies and location of residence than other parasite parameters such as growth rate or mean parasite density. Compared to observational field-based studies in children where 0.8% of the variability in malaria outcome was observed to be explained by anti-schizont antibodies, in the CHMI model the dichotomized anti-schizont antibodies explained 17% of the variability.

Conclusions

The CHMI model is highly effective in studying markers of naturally acquired immunity to malaria.

Trial registration Clinicaltrials.gov number NCT02739763. Registered 15 April 2016

A Roadmap for Building Data Science Capacity for Health Discovery and Innovation in Africa

Technological advances now make it possible to generate diverse, complex and varying sizes of data in a wide range of applications from business to engineering to medicine. In the health sciences, in particular, data are being produced at an unprecedented rate across the full spectrum of scientific inquiry spanning basic biology, clinical medicine, public health and health care systems. Leveraging these data can accelerate scientific advances, health discovery and innovations. However, data are just the raw material required to generate new knowledge, not knowledge on its own, as a pile of bricks would not be mistaken for a building. In order to solve complex scientific problems, appropriate methods, tools and technologies must be integrated with domain knowledge expertise to generate and analyze big data. This integrated interdisciplinary approach is what has become to be widely known as data science. Although the discipline of data science has been rapidly evolving over the past couple of decades in resource-rich countries, the situation is bleak in resource-limited settings such as most countries in Africa primarily due to lack of well-trained data scientists. In this paper, we highlight a roadmap for building capacity in health data science in Africa to help spur health discovery and innovation, and propose a sustainable potential solution consisting of three key activities: a graduate-level training, faculty development, and stakeholder engagement. We also outline potential challenges and mitigating strategies.

High efficacy of microbial larvicides for malaria vectors control in the city of Yaounde Cameroon following a cluster randomized trial

The rapid expansion of insecticide resistance and outdoor malaria transmission are affecting the efficacy of current malaria control measures. In urban settings, where malaria transmission is focal and breeding habitats are few, fixed and findable, the addition of anti-larval control measures could be efficient for malaria vector control. But field evidences for this approach remains scarce. Here we provide findings of a randomized-control larviciding trial conducted in the city of Yaoundé that support the efficacy of this approach. A two arms random control trial design including 26 clusters of 2 to 4 km2 each (13 clusters in the intervention area and 13 in the non-intervention area) was used to assess larviciding efficacy. The microbial larvicide VectoMax combining Bacillus thuringiensis var israelensis (Bti) and Bacillus sphaericus in a single granule was applied every 2 weeks in all standing water collection points. The anopheline density collected using CDC light traps was used as the primary outcome, secondary outcomes included the entomological inoculation rate, breeding habitats with anopheline larvae, and larval density. Baseline entomological data collection was conducted for 17 months from March 2017 to July 2018 and the intervention lasted 26 months from September 2018 to November 2020. The intervention was associated with a reduction of 68% of adult anopheline biting density and of 79% of the entomological inoculation rate (OR 0.21; 95% CI 0.14-0.30, P < 0.0001). A reduction of 68.27% was recorded for indoor biting anophelines and 57.74% for outdoor biting anophelines. No impact on the composition of anopheline species was recorded. A reduction of over 35% of adult Culex biting densities was recorded. The study indicated high efficacy of larviciding for reducing malaria transmission intensity in the city of Yaoundé. Larviciding could be part of an integrated control approach for controlling malaria vectors and other mosquito species in the urban environment.

Development of a Multiplex Loop-Mediated Isothermal Amplification (LAMP) Method for Simultaneous Detection of Spotted Fever Group Rickettsiae and Malaria Parasites by Dipstick DNA Chromatography

Spotted fever group (SFG) rickettsiae causes febrile illness in humans worldwide. Since SFG rickettsiosis’s clinical presentation is nonspecific, it is frequently misdiagnosed as other febrile diseases, especially malaria, and complicates proper treatment. Aiming at rapid, simple, and simultaneous detection of SFG Rickettsia spp. and Plasmodium spp., we developed a novel multiple pathogen detection system by combining a loop-mediated isothermal amplification (LAMP) method and dipstick DNA chromatography technology. Two primer sets detecting SFG Rickettsia spp. and Plasmodium spp. were mixed, and amplified products were visualized by hybridizing to dipstick DNA chromatography. The multiplex LAMP with dipstick DNA chromatography distinguished amplified Rickettsia and Plasmodium targeted genes simultaneously. The determined sensitivity using synthetic nucleotides was 1000 copies per reaction for mixed Rickettsia and Plasmodium genes. When genomic DNA from in vitro cultured organisms was used, the sensitivity was 100 and 10 genome equivalents per reaction for Rickettsia monacensis and Plasmodium falciparum, respectively. Although further improvement will be required for more sensitive detection, our developed simultaneous diagnosis technique will contribute to the differential diagnosis of undifferentiated febrile illness caused by either SFG Rickettsia spp. or Plasmodium spp. in resource-limited endemic areas. Importantly, this scheme is potentially versatile for the simultaneous detection of diverse infectious diseases.

The relationship between facility-based malaria test positivity rate and community-based parasite prevalence

INTRODUCTION

Malaria surveillance is a key pillar in the control of malaria in Africa. The value of using routinely collected data from health facilities to define malaria risk at community levels remains poorly defined.

METHODS

Four cross-sectional parasite prevalence surveys were undertaken among residents at 36 enumeration zones in Kilifi county on the Kenyan coast and temporally and spatially matched to fever surveillance at 6 health facilities serving the same communities over 12 months. The age-structured functional form of the relationship between test positivity rate (TPR) and community-based parasite prevalence (PR) was explored through the development of regression models fitted by alternating the linear, exponential and polynomial terms for PR. The predictive ranges of TPR were explored for PR endemicity risk groups of control programmatic value using cut-offs of low (PR <5%) and high (PR ≥ 30%) transmission intensity.

RESULTS

Among 28,134 febrile patients encountered for malaria diagnostic testing in the health facilities, 12,143 (43.2%: 95% CI: 42.6%, 43.7%) were positive. The overall community PR was 9.9% (95% CI: 9.2%, 10.7%) among 6,479 participants tested for malaria. The polynomial model was the best fitting model for the data that described the algebraic relationship between TPR and PR. In this setting, a TPR of ≥ 49% in all age groups corresponded to an age-standardized PR of ≥ 30%, while a TPR of < 40% corresponded to an age-standardized PR of < 5%.

CONCLUSION

A non-linear relationship was observed between the relative change in TPR and changes in the PR, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission. However, larger, more spatially diverse data series using routinely collected TPR data matched to community-based infection prevalence data are required to explore the more practical implications of using TPR as a replacement for community PR.