Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data

Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016-2021

BACKGROUND

Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana.

METHODS

The study used 2016-2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods.

RESULTS

A total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = - 13.82-15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean - 1.82, 95% credible interval = - 16.59-12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time.

CONCLUSION

This study identified high malaria risk districts in Ghana where urgent and targeted control efforts are required. Noticeable changes were also observed in malaria risk for certain districts over some periods in the study. The findings provide an effective, actionable tool to arm policymakers and programme managers in their efforts to reduce malaria risk and its associated morbidity and mortality in line with the Sustainable Development Goals (SDG) 3.2 for limited public health resource settings, where universal intervention across all districts is practically impossible.

Fever in focus: Symptoms, diagnoses and treatment of febrile children in Ghana-A longitudinal hospital study

BACKGROUND

Healthcare resources are often limited in areas of sub-Saharan Africa. This makes accurate and timely diagnoses challenging and delays treatment of childhood febrile illness. We explored longitudinal characteristics related to symptoms, diagnosis and treatment of hospitalised febrile children in a rural area of Ghana highly endemic for malaria.

METHODS

Febrile children under 15 years, admitted to the study hospital paediatric ward, were recruited to the study and clinical data were collected throughout hospitalisation. Descriptive statistics were reported for all cases; for longitudinal analyses, a subset of visits with limited missing data was used.

RESULTS

There were 801 hospitalised children included in longitudinal analyses. Malaria (n = 581, 73%) and sepsis (n = 373, 47%) were the most prevalent suspected diagnoses on admission. One-third of malaria suspected diagnoses (n = 192, 33%) were changed on the discharge diagnosis, compared to 84% (n = 315) of sepsis suspected diagnoses. Among malaria-only discharge diagnoses, 98% (n/N = 202/207) received an antimalarial and 33% (n/N = 69/207) an antibiotic; among discharge diagnoses without malaria, 28% (n/N = 108/389) received an antimalarial and 83% (n/N = 324/389) an antibiotic.

CONCLUSIONS

Suspected diagnoses were largely based on clinical presentation and were frequently changed; changed diagnoses were associated with lingering symptoms, underscoring the need for faster and more accurate diagnostics. Medications were over-prescribed regardless of diagnosis stability, possibly because of a lack of confidence in suspected diagnoses. Thus, better diagnostic tools are needed for childhood febrile illnesses to enhance the accuracy of and confidence in diagnoses, and to cut down unjustified medication use, reducing the risk of antimicrobial and malaria resistance.

Molecular speciation of Plasmodium and multiplicity of P. falciparum infection in the Central region of Ghana

Malaria is endemic in the Central region of Ghana, however, the ecological and the seasonal variations of Plasmodium population structure and the intensity of malaria transmission in multiple sites in the region have not been explored. In this cross-sectional study, five districts in the region were involved. The districts were Agona Swedru, Assin Central and Gomoa East (representing the forest zone) and Abura-Asebu-Kwamankese and Cape Coast representing the coastal zone. Systematically, blood samples were collected from patients with malaria. The malaria status was screened with a rapid diagnostic test (RDT) kit (CareStart manufactured by Access Bio in Somerset, USA) and the positive ones confirmed microscopically. Approximately, 200 μL of blood was used to prepare four dried blood spots of 50μL from each microscopy positive sample. The Plasmodium genome was sequenced at the Malaria Genome Laboratory (MGL) of Wellcome Sanger Institute (WSI), Hinxton, UK. The single nucleotide polymorphisms (SNPs) in the parasite mitochondria (PfMIT:270) core genome aided the species identification of Plasmodium. Subsequently, the complexity of infection (COI) was determined using the complexity of infection likelihood (COIL) computational analysis. In all, 566 microscopy positive samples were sequenced. Of this number, Plasmodium genome was detected in 522 (92.2%). However, whole genome sequencing was successful in 409/522 (72.3%) samples. In total, 516/522 (98.8%) of the samples contained P. falciparum mono-infection while the rest (1.2%) were either P. falciparum/P. ovale (Pf/Po) (n = 4, 0.8%) or P. falciparum/P. malariae/P. vivax (Pf/Pm/Pv) mixed-infection (n = 2, 0.4%). All the four Pf/Po infections were identified in samples from the Assin Central municipality whilst the two Pf/Pm/Pv triple infections were identified in Abura-Asebu-Kwamankese district and Cape Coast metropolis. Analysis of the 409 successfully sequenced genome yielded between 1-6 P. falciparum clones per individual infection. The overall mean COI was 1.78±0.92 (95% CI: 1.55-2.00). Among the study districts, the differences in the mean COI between ecological zones (p = 0.0681) and seasons (p = 0.8034) were not significant. However, regression analysis indicated that the transmission of malaria was more than twice among study participants aged 15-19 years (OR = 2.16, p = 0.017) and almost twice among participants aged over 60 years (OR = 1.91, p = 0.021) compared to participants between 20-59 years. Between genders, mean COI was similar except in Gomoa East where females recorded higher values. In conclusion, the study reported, for the first time, P. vivax in Ghana. Additionally, intense malaria transmission was found to be higher in the 15-19 and > 60 years, compared to other age groups. Therefore, active surveillance for P. vivax in Ghana and enhanced malaria control measures in the 15-19 year group years and those over 60 years are recommended.

Evaluation of the malaria surveillance system - Adaklu District, Volta Region, Ghana, 2019

Objectives

We evaluated the malaria surveillance system in Adaklu District of the Volta Region of Ghana to determine if the system was meeting its objectives and assessed its usefulness and attributes.

Study design

Descriptive cross-sectional design was used in evaluating the surveillance system.

Methods

We interviewed stakeholders using a semi-structured questionnaire on case detection and reporting. We assessed the system attributes using the Centers for Disease Control and Prevention updated guidelines for evaluating public health surveillance systems. We extracted and reviewed malaria surveillance data from the District Health Management Information System 2. Summary statistics and direct content analysis were performed on quantitative and qualitative data respectively.

Results

Of the 80,441 suspected malaria cases recorded in Adaklu District from 2014 to 2018, 47,917 (59.6%) cases were confirmed. The system was meeting its objective of detecting malaria cases and monitoring trends in the population however, the system missed an epidemic in August 2016. Data generated from the surveillance system is used by the NMCP to aid in the distribution of logistics such as LLINs, RDT test kits, and track malaria control progress in the district. Staff at all levels were able to detect, confirm, treat and report malaria. All sub-districts/health facilities reported to the district and reports were all accurate and timely. The predictive value positive was 62.9%.

Conclusions

The malaria surveillance system in Adaklu District was useful and meeting its set objective of monitoring trends of malaria in the population. It was simple, flexible, acceptable and representative; however, the system was not detecting epidemics. The District Health Management Team should set alert and epidemic thresholds to help detect promptly epidemics of malaria in the district.

Spatio-temporal modelling of routine health facility data for malaria risk micro-stratification in mainland Tanzania

As malaria transmission declines, the need to monitor the heterogeneity of malaria risk at finer scales becomes critical to guide community-based targeted interventions. Although routine health facility (HF) data can provide epidemiological evidence at high spatial and temporal resolution, its incomplete nature of information can result in lower administrative units without empirical data. To overcome geographic sparsity of data and its representativeness, geo-spatial models can leverage routine information to predict risk in un-represented areas as well as estimate uncertainty of predictions. Here, a Bayesian spatio-temporal model was applied on malaria test positivity rate (TPR) data for the period 2017-2019 to predict risks at the ward level, the lowest decision-making unit in mainland Tanzania. To quantify the associated uncertainty, the probability of malaria TPR exceeding programmatic threshold was estimated. Results showed a marked spatial heterogeneity in malaria TPR across wards. 17.7 million people resided in areas where malaria TPR was high (≥ 30; 90% certainty) in the North-West and South-East parts of Tanzania. Approximately 11.7 million people lived in areas where malaria TPR was very low (< 5%; 90% certainty). HF data can be used to identify different epidemiological strata and guide malaria interventions at micro-planning units in Tanzania. These data, however, are imperfect in many settings in Africa and often require application of geo-spatial modelling techniques for estimation.

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 in pregnancy control and pregnancy outcomes: a decade's overview using Ghana's DHIMS II data

Background

Malaria in pregnancy control interventions have been implemented through antenatal care services for more than 2 decades in Ghana. The uptake of these interventions has seen steady improvement over the years. This has occurred within the context of decreasing global trends of malaria infection confirmed by decreasing malaria in pregnancy prevalence in Ghana. However, not much is known about how these improvements in interventions uptake and reduction in malaria infection prevalence have impacted pregnancy outcomes in the country. This study aimed at describing trends of maternal anaemia and low birth weight prevalence and uptake of malaria in pregnancy control interventions over the last decade using data from Ghana’s District Health Information Management System (DHIMS II).

Methods

Data from Ghana’s DHIMS II on variables of interest covering the period 2012 to 2021 was analysed descriptively using Microsoft Excel 365. Results were computed as averages and percentages and presented in tables and graphs.

Results

The prevalence of maternal anaemia at booking and at term and low birth weight increased marginally from 31.0%, 25.5% and 8.5% in 2012 to 36.6%, 31.9% and 9.5% in 2021 respectively. Severe anaemia prevalence at booking and at term remained under 2% over the study period. Women making at least 4 ANC visits, receiving at least 3 doses of intermittent preventive treatment of malaria and an insecticide-treated net increased from 77.0%, 41.4% and 4.1% in 2012 to 82%, 55.0% and 93.3% in 2021, respectively. Malaria test positivity rate reduced from 54.0% to 34.3% between 2014 and 2021 while women receiving iron and folate supplementation for 3 and 6 months rose from 43.0% and 25.5% to 89.7% and 61.8%, respectively between 2017 and 2021.

Conclusion

Maternal anaemia and low birth weight prevalence showed marginal upward trends over the last decade despite reduced malaria infection rate and improved uptake of malaria in pregnancy control interventions. There is room for improvement in current intervention implementation levels but the complex and multi-factorial aetiologies of maternal anaemia and low birth weight need urgent investigation and quantification to inform policy and practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04331-2.

Preponderance of vaccine-preventable diseases hotspots in northern Ghana: a spatial and space-time clustering analysis from 2010 to 2014

BACKGROUND

Vaccine-preventable diseases (VPDs) persist globally with a disproportionately high burden in Low and Middle-Income Countries (LMICs). Although this might be partly due to the failure to sustain vaccination coverage above 90% in some WHO regions, a more nuanced understanding of VPD transmission beyond vaccination coverage may unveil other important factors in VPD transmission and control. This study identified VPDs hotspots and explored their relationships with ecology, urbanicity and land-use variations (Artisanal and Small-scale Gold Mining (ASGM) activities) in Ghana.

METHODS

District-level disease count data from 2010 to 2014 from the Ghana Health Service (GHS) and population data from the Ghana Population and Housing Census (PHC) were used to determine clustering patterns of six VPDs (Measles, Meningitis, Mumps, Otitis media, Pneumonia and Tetanus). Spatial and space-time cluster analyses were implemented in SaTScan using the discrete Poisson model. P-values were estimated using a combination of sequential Monte Carlo, standard Monte Carlo, and Gumbel approximations.

RESULTS

The study found a preponderance for VPD hotspots in the northern parts of Ghana and northernmost ecological zones (Sudan Savannah and Guinea Savannah). Incidence of meningitis was higher in the Sudan Savannah ecological zone relative to: Tropical Rain Forest (p = 0.001); Semi Deciduous Forest (p < 0.0001); Transitional Zone (p < 0.0001); Coastal Savannah (p < 0.0001) and Guinea Savannah (p = 0.033). Except for mumps, which recorded a higher incidence in urban districts (p = 0.045), incidence of the other five VPDs did not differ across the urban-rural divide. Whereas spatial analysis suggested that some VPD hotspots (tetanus and otitis media) occur more frequently in mining districts in the southern part of the country, a Mann-Whitney U test revealed a higher incidence of meningitis in non-mining districts (p = 0.019). Pneumonia and meningitis recorded the highest (722.8 per 100,000) and least (0.8 per 100,000) incidence rates respectively during the study period.

CONCLUSION

This study shows a preponderance of VPD hotspots in the northern parts of Ghana and in semi-arid ecoclimates. The relationship between ASGM activities and VPD transmission in Ghana remains blurred and requires further studies with better spatial resolution to clarify.

The resting behavior of malaria vectors in different ecological zones of Ghana and its implications for vector control

BACKGROUND

In sub-Saharan Africa there is widespread use of long-lasting insecticidal nets and indoor residual spraying to help control the densities of malaria vectors and decrease the incidence of malaria. This study was carried out to investigate the resting behavior, host preference and infection with Plasmodium falciparum of malaria vectors in Ghana in the context of the increasing insecticide resistance of malaria vectors in sub-Saharan Africa.

METHODS

Indoor and outdoor resting anopheline mosquitoes were sampled during the dry and rainy seasons in five sites in three ecological zones [Sahel savannah (Kpalsogo, Pagaza, Libga); coastal savannah (Anyakpor); and forest (Konongo)]. Polymerase chain reaction-based molecular diagnostics were used to determine speciation, genotypes for knockdown resistance mutations (L1014S and L1014F) and the G119S ace1 mutation, specific host blood meal origins and sporozoite infection in the field-collected mosquitoes.

RESULTS

Anopheles gambiae sensu lato (s.l.) predominated (89.95%, n = 1718), followed by Anopheles rufipes (8.48%, n = 162) and Anopheles funestus s.l. (1.57%, n = 30). Sibling species of the Anopheles gambiae s.l. revealed Anopheles coluzzii accounted for 63% (95% confidence interval = 57.10-68.91) and 27% (95% confidence interval = 21.66-32.55) was Anopheles gambiae s. s.. The mean resting density of An. gambiae s.l. was higher outdoors (79.63%; 1368/1718) than indoors (20.37%; 350/1718) (Wilcoxon rank sum test, Z = - 4.815, P < 0.0001). The kdr west L1014F and the ace1 mutation frequencies were higher in indoor resting An. coluzzii and An. gambiae in the Sahel savannah sites than in the forest and coastal savannah sites. Overall, the blood meal analyses revealed that a larger proportion of the malaria vectors preferred feeding on humans (70.2%) than on animals (29.8%) in all of the sites. Sporozoites were only detected in indoor resting An. coluzzii from the Sahel savannah (5.0%) and forest (2.5%) zones.

CONCLUSIONS

This study reports high outdoor resting densities of An. gambiae and An. coluzzii with high kdr west mutation frequencies, and the presence of malaria vectors indoors despite the use of long-lasting insecticidal nets and indoor residual spraying. Continuous monitoring of changes in the resting behavior of mosquitoes and the implementation of complementary malaria control interventions that target outdoor resting Anopheles mosquitoes are necessary in Ghana.

Trends of malaria infection in pregnancy in Ghana over the past two decades: a review

Background

There has been a global decline in malaria transmission over the past decade. However, not much is known of the impact of this observation on the burden of malaria infection in pregnancy in endemic regions including Ghana. A narrative review was undertaken to help describe trends in malaria infection in pregnancy in Ghana. Among others, such information is important in showing any progress made in malaria in pregnancy control.

Methods

To describe trends in pregnancy-associated malaria infection in Ghana, a search and review of literature reporting data on the prevalence of asymptomatic Plasmodium falciparum infection in pregnancy was conducted.

Results

Thirty-six (36) studies, conducted over 1994–2019, were included in the review. In the northern savannah zone with largely seasonal malaria transmission, prevalence appeared to reduce from about 50–60% in 1994–2010 to 13–26% by 2019. In the middle transitional/forest zone, where transmission is perennial with peaks in the rainy season, prevalence apparently reduced from 60% in the late 1990 s to about 5–20% by 2018. In the coastal savannah area, there was apparent reduction from 28 to 35% in 2003–2010 to 5–11% by 2018–2019. The burden of malaria infection in pregnancy continues to be highest among teenagers and younger-aged pregnant women and paucigravidae.

Conclusions

There appears to be a decline in asymptomatic parasite prevalence in pregnancy in Ghana though this has not been uniform across the different transmission zones. The greatest declines were noticeably in urban settings. Submicroscopic parasitaemia remains a challenge for control efforts. Further studies are needed to evaluate the impact of the reduced parasite prevalence on maternal anaemia and low birthweight and to assess the local burden of submicroscopic parasitaemia in relation to pregnancy outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-04031-3.

Assessing the effectiveness of malaria interventions at the regional level in Ghana using a mathematical modelling application

Supporting malaria control with interfaced applications of mathematical models that enables investigating effectiveness of various interventions as well as their cost implications could be useful. Through their usage for planning, these applications may improve the prospects of attaining various set targets such as those of the National Strategic Plan policies for malaria control in Ghana. A malaria model was adapted and used for simulating the incidence of malaria in various regions of Ghana. The model and its application were developed by the Modelling and Simulation Hub Africa and calibrated using district level data in Ghana from 2012 to 2018. Average monthly rainfall at the zonal level was fitted to trigonometric functions for each ecological zone using least squares approach. These zonal functions were then used as forcing functions. Subsequently, various intervention packages were investigated to observe their impact on averting malaria incidence by 2030. Increased usage of bednets but not only coverage levels, predicted a significant proportion of cases of malaria averted in all regions. Whereas, improvements in the health system by way of health seeking, testing and treatment predicted a decline in incidence largely in all regions. With an increased coverage of SMC, to include higher age groups, a modest proportion of cases could be averted in populations of the Guinea savannah. Indoor residual spraying could also benefit populations of the Transitional forest and Coastal savannah as its impact is significant in averting incidence. Enhancing bednet usage to at least a doubling of the current usage levels and deployed in combination with various interventions across regions predicted significant reductions, in malaria incidence. Regions of the Transitional forest and Coastal savannah could also benefit from a drastic decline in incidence following a gradual introduction of indoor residual spraying on a sustained basis.

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.

Identifying Plasmodium falciparum transmission patterns through parasite prevalence and entomological inoculation rate

Background

Monitoring malaria transmission is a critical component of efforts to achieve targets for elimination and eradication. Two commonly monitored metrics of transmission intensity are parasite prevalence (PR) and the entomological inoculation rate (EIR). Comparing the spatial and temporal variations in the PR and EIR of a given geographical region and modelling the relationship between the two metrics may provide a fuller picture of the malaria epidemiology of the region to inform control activities.

Methods

Using geostatistical methods, we compare the spatial and temporal patterns of Plasmodium falciparum EIR and PR using data collected over 38 months in a rural area of Malawi. We then quantify the relationship between EIR and PR by using empirical and mechanistic statistical models.

Results

Hotspots identified through the EIR and PR partly overlapped during high transmission seasons but not during low transmission seasons. The estimated relationship showed a 1-month delayed effect of EIR on PR such that at lower levels of EIR, increases in EIR are associated with rapid rise in PR, whereas at higher levels of EIR, changes in EIR do not translate into notable changes in PR.

Conclusions

Our study emphasises the need for integrated malaria control strategies that combine vector and human host managements monitored by both entomological and parasitaemia indices.

Funding

This work was supported by Stichting Dioraphte grant number 13050800.

Mapping socioeconomic inequalities in malaria in Sub-Sahara African countries

Despite reductions in malaria incidence and mortality across Sub-Saharan (SSA) countries, malaria control and elimination efforts are currently facing multiple global challenges such as climate and land use change, invasive vectors, and disruptions in healthcare delivery. Although relationships between malaria risks and socioeconomic factors have been widely demonstrated, the strengths and variability of these associations have not been quantified across SSA. In this study, we used data from population-based malaria indicator surveys in SSA countries to assess spatial trends in relative and absolute socioeconomic inequalities, analyzed as social (mothers’ highest educational level—MHEL) and economic (wealth index—WI) inequalities in malaria prevalence. To capture spatial variations in socioeconomic (represented by both WI and MHEL) inequalities in malaria, we calculated both the Slope Index of Inequality (SII) and Relative Index of Inequality (RII) in each administrative region. We also conducted cluster analyses based on Local Indicator of Spatial Association (LISA) to consider the spatial auto-correlation in SII and RII across regions and countries. A total of 47,404 participants in 1874 Primary Sampling Units (PSU) were analyzed across the 13 SSA countries. Our multi-country assessment provides estimations of strong socioeconomic inequalities between and within SSA countries. Such within- and between- countries inequalities varied greatly according to the socioeconomic metric and the scale used. Countries located in Eastern Africa showed a higher median Slope Index of Inequality (SII) and Relative Index of Inequality (RII) in malaria prevalence relative to WI in comparison to countries in other locations across SSA. Pockets of high SII in malaria prevalence in relation to WI and MHEL were observed in the East part of Africa. This study was able to map this wide range of malaria inequality metrics at a very local scale and highlighted the spatial clustering patterns of pockets of high and low malaria inequality values.

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.

Population structure and diversity of Plasmodium falciparum in children with asymptomatic malaria living in different ecological zones of Ghana

BACKGROUND

Genetic diversity in Plasmodium falciparum populations can be used to describe the resilience and spatial distribution of the parasite in the midst of intensified intervention efforts. This study used microsatellite analysis to evaluate the genetic diversity and population dynamics of P. falciparum parasites circulating in three ecological zones of Ghana.

METHODS

A total of 1168 afebrile children aged between 3 to 13 years were recruited from five (5) Primary schools in 3 different ecological zones (Sahel (Tamale and Kumbungu), Forest (Konongo) and Coastal (Ada and Dodowa)) of Ghana. Asymptomatic malaria parasite carriage was determined using microscopy and PCR, whilst fragment analysis of 6 microsatellite loci was used to determine the diversity and population structure of P. falciparum parasites.

RESULTS

Out of the 1168 samples examined, 16.1 and 39.5% tested positive for P. falciparum by microscopy and nested PCR respectively. The genetic diversity of parasites in the 3 ecological zones was generally high, with an average heterozygosity (He) of 0.804, 0.787 and 0.608 the rainy (peak) season for the Sahel, Forest and Coastal zones respectively. The mean He for the dry (off-peak) season were 0.562, 0.693 and 0.610 for the Sahel, Forest and Coastal zones respectively. Parasites from the Forest zone were more closely related to those from the Sahel than from the Coastal zone, despite the Coastal zone being closer in physical distance to the Forest zone. The fixation indexes among study sites ranged from 0.049 to 0.112 during the rainy season and 0.112 to 0.348 during the dry season.

CONCLUSION

A large asymptomatic parasite reservoir was found in the school children during both rainy and dry seasons, especially those in the Forest and Sahel savannah zones where parasites were also found to be related compared to those from the Coastal zone. Further studies are recommended to understand why despite the roll out of several malaria interventions in Ghana, high transmission still persist.

Malaria micro-stratification using routine surveillance data in Western Kenya

BACKGROUND

There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya.

METHODS

Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility.

RESULTS

The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.

CONCLUSION

The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

Accounting for regional transmission variability and the impact of malaria control interventions in Ghana: a population level mathematical modelling approach

BACKGROUND

This paper investigates the impact of malaria preventive interventions in Ghana and the prospects of achieving programme goals using mathematical models based on regionally diverse climatic zones of the country.

METHODS

Using data from the District Health Information Management System of the Ghana Health Service from 2008 to 2017, and historical intervention coverage levels, ordinary non-linear differential equations models were developed. These models incorporated transitions amongst various disease compartments for the three main ecological zones in Ghana. The Approximate Bayesian Computational sampling approach, with a distance based rejection criteria, was adopted for calibration. A leave-one-out approach was used to validate model parameters and the most sensitive parameters were evaluated using a multivariate regression analysis. The impact of insecticide-treated bed nets and their usage, and indoor residual spraying, as well as their protective efficacy on the incidence of malaria, was simulated at various levels of coverage and protective effectiveness in each ecological zone to investigate the prospects of achieving goals of the Ghana malaria control strategy for 2014-2020.

RESULTS

Increasing the coverage levels of both long-lasting insecticide-treated bed nets and indoor residual spraying activities, without a corresponding increase in their recommended utilization, does not impact highly on averting predicted incidence of malaria. Improving proper usage of long-lasting insecticide-treated bed nets could lead to substantial reductions in the predicted incidence of malaria. Similar results were obtained with indoor residual spraying across all ecological zones of Ghana.

CONCLUSIONS

Projected goals set in the national strategic plan for malaria control 2014-2020, as well as World Health Organization targets for malaria pre-elimination by 2030, are only likely to be achieved if a substantial improvement in treated bed net usage is achieved, coupled with targeted deployment of indoor residual spraying with high community acceptability and efficacy.

Insecticide resistance in indoor and outdoor-resting Anopheles gambiae in Northern Ghana

BACKGROUND

Selection pressure from continued exposure to insecticides drives development of insecticide resistance and changes in resting behaviour of malaria vectors. There is need to understand how resistance drives changes in resting behaviour within vector species. The association between insecticide resistance and resting behaviour of Anopheles gambiae sensu lato (s.l.) in Northern Ghana was examined.

METHODS

F1 progenies from adult mosquitoes collected indoors and outdoors were exposed to DDT, deltamethrin, malathion and bendiocarb using WHO insecticide susceptibility tests. Insecticide resistance markers including voltage-gated sodium channel (Vgsc)-1014F, Vgsc-1014S, Vgsc-1575Y, glutathione-S-transferase epsilon 2 (GSTe2)-114T and acetylcholinesterase (Ace1)-119S, as well as blood meal sources were investigated using PCR methods. Activities of metabolic enzymes, acetylcholine esterase (AChE), non-specific β-esterases, glutathione-S-transferase (GST) and monooxygenases were measured from unexposed F1 progenies using microplate assays.

RESULTS

Susceptibility of Anopheles coluzzii to deltamethrin 24 h post-exposure was significantly higher in indoor (mortality = 5%) than outdoor (mortality = 2.5%) populations (P = 0.02). Mosquitoes were fully susceptible to malathion (mortality: indoor = 98%, outdoor = 100%). Susceptibility to DDT was significantly higher in outdoor (mortality = 9%) than indoor (mortality = 0%) mosquitoes (P = 0.006). Mosquitoes were also found with suspected resistance to bendiocarb but mortality was not statistically different (mortality: indoor = 90%, outdoor = 95%. P = 0.30). Frequencies of all resistance alleles were higher in F1 outdoor (0.11-0.85) than indoor (0.04-0.65) mosquito populations, while Vgsc-1014F in F0 An. gambiae sensu stricto (s.s) was significantly associated with outdoor-resting behaviour (P = 0.01). Activities of non-specific β-esterase enzymes were significantly higher in outdoor than indoor mosquitoes (Mean enzyme activity: Outdoor = : 1.70/mg protein; Indoor = 1.35/mg protein. P < 0.0001). AChE activity was also more elevated in outdoor (0.62/mg protein) than indoor (0.57/mg protein) mosquitoes but this was not significant (P = 0.08). Human blood index (HBI) was predominantly detected in indoor (18%) than outdoor mosquito populations (3%).

CONCLUSIONS

The overall results did not establish that there was a significant preference of resistant malaria vectors to solely rest indoors or outdoors, but varied depending on the resistant alleles present. Phenotypic resistance was higher in indoor than outdoor-resting mosquitoes, but genotypic and metabolic resistance levels were higher in outdoor than the indoor populations. Continued monitoring of changes in resting behaviour within An. gambiae s.l. populations is recommended.

Evaluating the Effects of Climate and Environmental Factors on Under-5 Children Malaria Spatial Distribution Using Generalized Additive Models (GAMs)

Although malaria burden has declined globally following scale up of intervention, the disease has remained a leading cause of hospitalization and deaths among children aged under-5 years in Nigeria. Malaria is known to be related to climate and environmental conditions. Previous research has usually studied the effects of these factors, neglecting possible correlation between them, high correlation among variables is a source of multicollinearity that induces overfitting in regression modelling. In this paper, a factor analysis was first introduced to circumvent the issue of multicollinearity and a Generalized Additive Model (GAM) was subsequently explored to identify the important risk factors that might influence the prevalence of childhood malaria in Nigeria. The GAM incorporated the complexity of the survey data, while simultaneously modelling the nonlinear and spatial random effects to allow a more precise identification of the major malaria risk factors that influence the geographical distribution of the disease. From our findings, the three latent factor components (constituted by humidity, precipitation, potential evapotranspiration, and wet days/maximum and minimum temperature/proximity to permanent waters, respectively) were significantly associated with malaria prevalence. Our analysis also detected statistically significant and nonlinear effect of altitude: the risk of malaria increased with lower values but declined sharply with higher values. A significant spatial variability in under-5 malaria prevalence across the survey clusters was also observed; malaria burden was higher in the northern part of Nigeria. Investigating the impact of important risk factors and geographical location on childhood malaria is of high relevance for the sustainable development goals (SDGs) 2015–2030 Agenda on malaria eradication, and we believe that the information obtained from this study and the generated risk maps can be useful to effectively target intervention efforts to high-risk areas based on climate and environmental context.

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012

Background

In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal and to identify the meteorological, environmental, and preventive factors that influence this variation.

Methods

This study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central Senegal (total population approximately 500,000) as part of a trial of seasonal malaria chemoprevention (SMC). Data on weekly rainfall and annual vegetation types were obtained for each village through remote sensing. The time series of weekly malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. Malaria hotspots were detected during each transmission period with the SaTScan method. The effects of rainfall, vegetation type, and SMC intervention on the spatio-temporal variation of malaria hotspots were assessed using a General Additive Mixed Model.

Results

The malaria incidence for the entire area varied between 0 and 115.34 cases/100,000 person weeks during the study period. During high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. During low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. Villages with SMC were less likely to be hotspots (OR = 0.48, IC95%: 0.33–0.68). The association between rainfall and hotspot status was non-linear and depended on both vegetation type and amount of rainfall. The association between village location in the study area and hotspot status was also shown.

Conclusion

In our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. By taking into consideration the environmental and meteorological characteristics common to all hotspots, monitoring of these factors could lead targeted public health interventions at the local level. Moreover, spatial hotspots and foci of malaria persisting during LTPs need to be further addressed.

Trial registration

The data used in this work were obtained from a clinical trial registered on July 10, 2008 at www.clinicaltrials.gov under NCT00712374.

Quantifying Seasonal Variation in Insecticide-Treated Net Use among Those with Access

Seasonal variation in the proportion of the population using an insecticide-treated net (ITN) is well documented and is widely believed to be dependent on mosquito abundance and heat, driven by rainfall and temperature. However, seasonal variation in ITN use has not been quantified controlling for ITN access. Demographic and Health Survey and Malaria Indicator Survey datasets, their georeferenced data, and public rainfall and climate layers were pooled for 21 countries. Nine rainfall typologies were developed from rainfall patterns in Köppen climate zones. For each typology, the odds of ITN use among individuals with access to an ITN within their households (“ITN use given access”) were estimated for each month of the year, controlling for region, wealth quintile, residence, year, temperature, and malaria parasitemia level. Seasonality of ITN use given access was observed over all nine rainfall typologies and was most pronounced in arid climates and less pronounced where rainfall was relatively constant throughout the year. Peak ITN use occurred 1–3 months after peak rainfall and corresponded with peak malaria incidence and average malaria transmission season. The observed lags between peak rainfall and peak ITN use given access suggest that net use is triggered by mosquito density. In equatorial areas, ITN use is likely to be high year-round, given the presence of mosquitoes and an associated year-round perceived malaria risk. These results can be used to inform behavior change interventions to improve ITN use in specific times of the year and to inform geospatial models of the impact of ITNs on transmission.

Prevalence of Asymptomatic Malaria among Children in the Tamale Metropolis: How Does the PfHRP2 CareStart™ RDT Perform against Microscopy?

Background

Asymptomatic carriage of the malaria parasites, likewise its misdiagnosis, especially false negatives, due to the use of substandard rapid diagnosis tests (RDTs) has been shown to hinder the progress of the fight against malaria.

Method

The study assessed the prevalence of asymptomatic malaria as well as the performance of Plasmodium falciparum-specific protein and histidine-rich protein 2 (PfHRP2) CareStart™ RDT against standard microscopy in the detection of malaria infection among 345 children (1–15 yrs) from two (2) basic schools in Tamale Metropolis.

Results

From the microscopy (considered as gold standard), prevalence of malaria among the asymptomatic children was found to be 2.6%, with sensitivity and specificity of CareStart™ RDT in detecting P. falciparum infections found to be 55.6% and 93.8%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) of CareStart™ RDT were found to be 19.23% and 98.45%, respectively. There was an evidence showing a significant relation between CareStart™ RDT and microscopy in determining malaria infection (χ² = 30.579, p < 0.001).

Conclusion

Prevalence of asymptomatic malaria among children was found to be 2.6%. The study reported low sensitivity and PPV for PfHRP2 CareStart™ RDT in an asymptomatic population at instances of low parasitaemia.