Geostatistical analysis and mapping of malaria risk in children of Mozambique

Spatial distribution and determinants of anemia among under-five children in Mozambique

Worldwide, anemia in under-five children is a serious public health problem that causes significant morbidity and mortality. It also negatively impacts children's physical growth, focus, memory, and academic performance. Despite this, there is a paucity of up-to-date information on the spatial distribution and determinants of under-five anemia in Mozambique. Therefore, this study aimed to assess the spatial variation and determinates of anemia among under-five children in Mozambique by using the most recent demographic and health survey data. A cross-sectional study was conducted using the most recent demographic and health survey data of Mozambique. A total weighted sample of 3127 under-five children was included in the study. Spatial SaTScan statistics were done using Kuldroff's SaTScan version 9.6 software. ArcGIS version 10.7 software is used to visualize the spatial distribution of under-five anemia. A multilevel mixed-effects logistic regression analysis was employed to identify the determinants of under-five anemia. The level of statistical significance was declared at a p-value of < 0.05. Overall, the prevalence of anemia among under-five children in Mozambique was 49.46% (95% CI 47.70-51.21). Under-five anemia was not evenly distributed across the country; a higher distribution was observed in Zambezia, Nampula, Safala, and the southern part of Gaza; fewer cold spots were observed in the western and southern parts of Niassa, the eastern part of Tete, the western part of Manica, and Maputo City. In spatial scan statistics, children in the most likely cluster were 1.58 times more likely to be anemic than those living outside the window (RR = 1.58, P-value < 0.001). Children with fathers with no formal education, children from anemic mothers, children whose mothers are underweight, children residing in the Zambzia region, children residing in the Nampula region, and children residing in the Niassa region were significantly associated with under-five anemia in Mozambique. The burden of under-five anemia in Mozambique is higher and distributed non-randomly across regions. Maternal anemia, underweighted mothers, husband education, and regions in Mozambique were found to be significant determinants of anemia in under-five children. Improving the nutritional status of mothers and interventions to address maternal anemia, with special attention to the Nampula and Zambzia regions, are recommended to reduce under-five anemia in Mozambique.

The association between infrastructure damage in the aftermath of Cyclone Idai and malaria risk in Sofala Province, Mozambique: an ecological study

BACKGROUND

In April 2019, Mozambique was hit by Cyclone Idai leaving substantial damage to infrastructure and nearly two million people in need of humanitarian assistance. Malaria risk has been associated with living in a rural setting, vicinity to water, and household structure, all factors which are impacted by severe storms. This study quantified the association between damage to infrastructure (health care facilities and schools) following Cyclone Idai and malaria outcomes: malaria incidence, severe malaria, and administration of intermittent preventative treatment in pregnancy (IPTp) in Sofala Province, Mozambique.

METHODS

To quantify infrastructure damage, historical satellite imagery was assessed visually using Google Earth Pro®. Damage to 66 school and 105 health centres was assessed for severity and duration. Location data was imported to QGIS and joined with district level data on malaria outcomes and environmental covariates. Multivariable Poisson regression models were used to quantify the associations between facility damage and malaria incidence and severe malaria. Generalized linear models were used to determine the association between facility damage and changes in malaria incidence and administration of IPTp from 2018 to 2019.

RESULTS

An increase in facility damage was associated with an increase in malaria incidence and severe malaria. An increase in proportion of facilities damaged by 10% was associated with a 7.3% (95% CI 6.8-7.8%) increase in malaria incidence. Risk of severe malaria was 2.16 (95% CI 1.42-3.32) times higher in districts with any damage compared to those with no damage. However, proportional facility damage was associated with decreased malaria incidence and increased access to IPTp from 2018 to 2019, but these were not statistically significant.

CONCLUSION

An increase in proportion of facilities damaged following Cyclone Idai was associated with increased risk of malaria and severe malaria at the district level. This may be a function of decreased access to healthcare and an increased exposure to risk factors for malaria. A non-statistically significant decrease in malaria incidence was also found at the district level from 2018 to 2019, indicating that malaria may have been underreported in 2019, likely again a function of decreased access to healthcare.

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

Malaria ranks high among prevalent and ravaging infectious diseases in sub-Saharan Africa (SSA). The negative impacts, disease burden, and risk are higher among children and pregnant women as part of the most vulnerable groups to malaria in Nigeria. However, the burden of malaria is not even in space and time. This study explores the spatial variability of malaria prevalence among children under five years (U5) in medium-sized rapidly growing city of Akure, Nigeria using model-based geostatistical modeling (MBG) technique to predict U5 malaria burden at a 100 × 100 m grid, while the parameter estimation was done using Monte Carlo maximum likelihood method. The non-spatial logistic regression model shows that U5 malaria prevalence is significantly influenced by the usage of insecticide-treated nets-ITNs, window protection, and water source. Furthermore, the MBG model shows predicted U5 malaria prevalence in Akure is greater than 35% at certain locations while we were able to ascertain places with U5 prevalence > 10% (i.e. hotspots) using exceedance probability modelling which is a vital tool for policy development. The map provides place-based evidence on the spatial variation of U5 malaria in Akure, and direction on where intensified interventions are crucial for the reduction of U5 malaria burden and improvement of urban health in Akure, Nigeria.

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.

Factors associated with the use of long-lasting insecticidal nets in pregnant women and mothers with children under five years of age in Gaza province, Mozambique

Malaria remains a major public health concern worldwide. Malaria is endemic in Mozambique, with seasonal fluctuations throughout the country. Although the number of malaria cases in Mozambique have dropped by 11% from 2020 to 2021, there are still hotspots in the country with persistent high incidence and low insecticide-treated bed net usage. The aim of this study is to evaluate the factors associated with the use of long-lasting insecticidal nets by pregnant women and women with children under 5 years old in two hotspot districts in the Gaza province, Mozambique. A descriptive, qualitative cross-sectional study was conducted between June 15th and 21st 2022. An in-depth interview process was conducted with pregnant women and mothers with children under five years old, exploring their beliefs, experiences, and perception of messages conveyed by health professionals when long-lasting insecticidal nets were being supplied. A total of 48 women participated (24 pregnant women and 24 women with children under 5 years). Most participants recognized the protective effects of long-lasting insecticidal nets in preventing malaria, and understood that women and children were high risk groups. The nets were reported to cause side effects and difficulty breathing by 100% of pregnant women, while 54.2% of mothers with children under 5 reported no side effects. The majority of women in both groups reported that their health professionals did not educate them about how to use or handle the nets properly. Only 16.7% of mothers with children under 5 received correct handling instructions. Providing clear, culturally sensitive, and practical information on the correct use of LLINs, as well as regular monitoring of their proper use, would be a great step forward for Mozambique's national malaria program.

Spatial Optimization Methods for Malaria Risk Mapping in Sub-Saharan African Cities Using Demographic and Health Surveys

Vector-borne diseases, such as malaria, are affected by the rapid urban growth and climate change in sub-Saharan Africa (SSA). In this context, intra-urban malaria risk maps act as a key decision-making tool for targeting malaria control interventions, especially in resource-limited settings. The Demographic and Health Surveys (DHS) provide a consistent malaria data source for mapping malaria risk at the national scale, but their use is limited at the intra-urban scale because survey cluster coordinates are randomly displaced for ethical reasons. In this research, we focus on predicting intra-urban malaria risk in SSA cities-Dakar, Dar es Salaam, Kampala and Ouagadougou-and investigate the use of spatial optimization methods to overcome the effect of DHS spatial displacement. We modeled malaria risk using a random forest regressor and remotely sensed covariates depicting the urban climate, the land cover and the land use, and we tested several spatial optimization approaches. The use of spatial optimization mitigated the effects of DHS spatial displacement on predictive performance. However, this comes at a higher computational cost, and the percentage of variance explained in our models remained low (around 30%-40%), which suggests that these methods cannot entirely overcome the limited quality of epidemiological data. Building on our results, we highlight potential adaptations to the DHS sampling strategy that would make them more reliable for predicting malaria risk at the intra-urban scale.

Population structure and genetic connectivity of Plasmodium falciparum in pre-elimination settings of Southern Africa

To accelerate malaria elimination in the Southern African region by 2030, it is essential to prevent cross-border malaria transmission. However, countries within the region are highly interconnected due to human migration that aids in the movement of the parasite across geographical borders. It is therefore important to better understand Plasmodium falciparum transmission dynamics in the region, and identify major parasite source and sink populations, as well as cross-border blocks of high parasite connectivity. We performed a meta-analysis using collated parasite allelic data generated by microsatellite genotyping of malaria parasites from Namibia, Eswatini, South Africa, and Mozambique (N = 5,314). The overall number of unique alleles was significantly higher (P ≤ 0.01) in Namibia (mean A = 17.3 ± 1.46) compared to South Africa (mean A = 12.2 ± 1.22) and Eswatini (mean A = 13.3 ± 1.27, P ≤ 0.05), whilst the level of heterozygosity was not significantly different between countries. The proportion of polyclonal infections was highest for Namibia (77%), and lowest for Mozambique (64%). A was significant population structure was detected between parasites from the four countries, and patterns of gene flow showed that Mozambique was the major source area and Eswatini the major sink area of parasites between the countries. This study showed strong signals of parasite population structure and genetic connectivity between malaria parasite populations across national borders. This calls for strengthening the harmonization of malaria control and elimination efforts between countries in the southern African region. This data also proves its potential utility as an additional surveillance tool for malaria surveillance on both a national and regional level for the identification of imported cases and/or outbreaks, as well as monitoring for the potential spread of anti-malarial drug resistance as countries work towards malaria elimination.

What are the pathways between poverty and malaria in sub-Saharan Africa? A systematic review of mediation studies

BACKGROUND

Malaria remains a major burden in sub-Saharan Africa (SSA). While an association between poverty and malaria has been demonstrated, a clearer understanding of explicit mechanisms through which socioeconomic position (SEP) influences malaria risk is needed to guide the design of more comprehensive interventions for malaria risk mitigation. This systematic review provides an overview of the current evidence on the mediators of socioeconomic disparities in malaria in SSA.

METHODS

We searched PubMed and Web of Science for randomised controlled trials, cohort, case-control and cross-sectional studies published in English between January 1, 2000 to May 31, 2022. Further studies were identified following reviews of reference lists of the studies included. We included studies that either (1) conducted a formal mediation analysis of risk factors on the causal pathway between SEP and malaria infections or (2) adjusted for these potential mediators as confounders on the association between SEP and malaria using standard regression models. At least two independent reviewers appraised the studies, conducted data extraction, and assessed risk of bias. A systematic overview is presented for the included studies.

RESULTS

We identified 41 articles from 20 countries in SSA for inclusion in the final review. Of these, 30 studies used cross-sectional design, and 26 found socioeconomic inequalities in malaria risk. Three formal mediation analyses showed limited evidence of mediation of food security, housing quality, and previous antimalarial use. Housing, education, insecticide-treated nets, and nutrition were highlighted in the remaining studies as being protective against malaria independent of SEP, suggesting potential for mediation. However, methodological limitations included the use of cross-sectional data, insufficient confounder adjustment, heterogeneity in measuring both SEP and malaria, and generally low or moderate-quality studies. No studies considered exposure mediator interactions or considered identifiability assumptions.

CONCLUSIONS

Few studies have conducted formal mediation analyses to elucidate pathways between SEP and malaria. Findings indicate that food security and housing could be more feasible (structural) intervention targets. Further research using well-designed longitudinal studies and improved analysis would illuminate the current sparse evidence into the pathways between SEP and malaria and adduce evidence for more potential targets for effective intervention.

Symptomatic and asymptomatic malaria prevalence and its determinant factors in pastoral communities of Waghemira Zone, Northeast Ethiopia: A community-based cross-sectional study

Background and Aims

Malaria elimination programs have also encountered numerous challenges, such as widespread asymptomatic carriers in endemic areas, which should be taken into account in malaria-control programs for effective transmission interruption. The purpose of this research was to determine the prevalence of symptomatic and asymptomatic malaria infections and associated factors, in pastoral communities.

Methods

A community-based cross-sectional study was conducted among selected districts in the Waghemra Zone, Northeast Ethiopia, from September to December 2022. A structured questionnaire was employed to collect sociodemographic data and associated risk factors. Plasmodium species were detected using light microscopy and a rapid diagnostic test. Data entry and analysis were carried out using SPSS version 26 software. The association between dependent and independent variables was explored by using multivariable logistic regression analyses. A statistically significant association was declared at a p-value of <0.05.

Results

The overall prevalence of malaria was 21.2% (134/633), with the predominant Plasmodium falciparum infections accounting for 67.8% (87/134). Among asymptomatic participants, 7.5% (34/451) and 10.2% (46/451) were diagnosed by rapid diagnostic test and light microscopy, respectively. On the other hand, the prevalence of symptomatic malaria was 44.5% (81/182) and 48.4% (88/182) as diagnosed by rapid diagnostic test and light microscopy, respectively. The presence of stagnant water near the houses, the utilization of insecticide-treated mosquito nets, the number of insecticide-treated mosquito nets, and outdoor stays at night were all positively linked with the prevalence of malaria.

Conclusions

The overall prevalence estimate for symptomatic and asymptomatic malaria was high. Malaria is still a public health problem in the study area. Malaria infection was associated with the presence of stagnant water near the houses, the utilization of insecticide-treated mosquito nets, the number of insecticide-treated mosquito nets, and outdoor stays at night. Improved access to all malaria interventions is needed to interrupt the transmission at the community level.

Optimizing Routine Malaria Surveillance Data in Urban Environments: A Case Study in Maputo City, Mozambique

In urban settings in malaria-endemic countries, malaria incidence is not well characterized and assumed to be typically very low and consisting largely of imported infections. In such contexts, surveillance systems should adapt to ensure that data are of sufficient spatial and temporal resolution to inform appropriate programmatic interventions. The aim of this research was to 1) assess spatial and temporal trends in reported malaria cases in Maputo City, Mozambique, using an expanded case notification form and 2) to determine how malaria surveillance can be optimized to characterize the local epidemiological context, which can then be used to inform targeted entomological investigations and guide implementation of localized malaria responses. This study took place in all six health facilities of KaMavota District in Maputo City, Mozambique. A questionnaire was administered to all confirmed cases from November 2019 to August 2021. Households of cases were retrospectively geolocated using local landmarks as reference. Overall, 2,380 malaria cases were reported, with the majority being uncomplicated (97.7%) and a median age of 21 years; 70.8% of cases had reported traveling outside the city in the past month with nine reporting traveling internationally. Maps of the 1,314 malaria cases that were geolocated showed distinct spatial patterns. The expanded case notification form enables a more granular overview of the malaria epidemiology in Maputo City; the geolocation data clearly show the areas where endemic transmission is likely, thus informing where resources should be prioritized. As urbanization is rapidly increasing in malaria endemic areas, identifying systems and key variables to collect ensures an operational way to characterize urban malaria through optimization of routine data to inform decision-making.

Characterizing human movement patterns using GPS data loggers in an area of persistent malaria in Zimbabwe along the Mozambique border

BACKGROUND

Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions.

METHODS

A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU^® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses.

RESULTS

From June 2016-May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight.

CONCLUSIONS

Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region.

Impact of mass distribution of insecticide-treated nets in Mozambique, 2012 to 2025: Estimates of child lives saved using the Lives Saved Tool

Malaria was the leading cause of post-neonatal deaths in Mozambique in 2017. The use of insecticide treated nets (ITNs) is recognized as one of the most effective ways to reduce malaria mortality in children. No previous analyses have estimated changes in mortality attributable to the scale-up of ITNs, accounting for provincial differences in mortality rates and coverage of health interventions. Based upon annual provincial ownership coverage of ITNs, the Lives Saved Tool (LiST), a multi-cause mathematical model, estimated under-5 lives saved attributable to increased household ITN coverage in 10 provinces of Mozambique between 2012 and 2018, and projected lives saved from 2019 to 2025 if 2018 coverage levels are sustained. An estimated 14,040 under-5 child deaths were averted between 2012 and 2018. If 2018 coverage levels are maintained until 2025, an additional 33,277 child deaths could be avoided. If coverage reaches at least 85% in all ten provinces by 2022, then a projected 36,063 child lives can be saved. From 2012 to 2018, the estimated number of lives saved was highest in Zambezia and Tete provinces. Increases in ITN coverage can save a substantial number of child lives in Mozambique. Without continued investment, thousands of avoidable child deaths will occur.

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.