China's hidden role in malaria control and elimination in Africa.

BACKGROUND: Insufficient funding is hindering the achievement of malaria elimination targets in Africa, despite the pressing need for increased investment in malaria control. While Western donors attribute their inaction to financial constraints, the global health community has limited knowledge of China's expanding role in malaria prevention. This knowledge gap arises from the fact that China does not consistently report its foreign development assistance activities to established aid transparency initiatives. Our work focuses on identifying Chinese-funded malaria control projects throughout Africa and linking them to official data on malaria prevalence. By doing so, we aim to shed light on China's contributions to malaria control efforts, analysing their investments and assessing their impact. This would provide valuable insights into the development of effective financing mechanisms for future malaria control in Africa. METHODS: Our research used AidData' s recently released Global Chinese Development Finance Dataset V.2.0 providing comprehensive coverage of all official sector Chinese development financing across Africa, from which we identify 224 Chinese-funded malaria projects in Sub-Saharan Africa (SSA) committed between 2002 and 2017. We conducted an analysis of the spending patterns by year, country and regions within Africa and compared it with data on population-adjusted malaria prevalence, sourced from the Malaria Atlas Project. RESULTS: Chinese-financed malaria projects Africa mainly focused on three areas: the provision of medical supplies (72.32%), the construction of basic health infrastructure (17.86%) and the deployment of anti-malaria experts (3.57%). Moreover, nearly 39% of the initiatives were concentrated in just four countries: the Democratic Republic of Congo, Central African Republic, Uganda and Liberia. Additionally, China's development financing amount showed a weak negative correlation (-0.2393) with population-weighted malaria prevalence. We concluded that the extent and direction of China's support are not adequately tailored to address malaria challenges in different countries. CONCLUSION: With China's increasing engagement in global health, it is anticipated that malaria control will continue to be a prominent priority on its development assistance agenda. This is attributed to China's vast expertise in malaria elimination, coupled with its substantial contribution as a major producer of malaria diagnostics and treatments.

Factors associated with fertility intentions among women living with and without human immunodeficiency virus in Zambia.

BACKGROUND: Zambia is one of the countries in sub-Saharan Africa with a high prevalence of human immunodeficiency virus among women of reproductive age. Notably, the literature shows that human immunodeficiency virus status is one of the factors that influence fertility intention among women of reproductive age. With increased access, uptake and coverage of anti retroviral therapy, there is a need to understand the influence of human immunodeficiency virus status on fertility intentions of women of reproductive age in Zambia. OBJECTIVES: The purpose of this study was to determine the fertility intentions of both mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus in Zambia. DESIGN: This study adopted a cross-sectional design using data collected by the Zambia Demographic and Health Survey conducted in 2018. The study sample comprised 7983 mothers in the reproductive age (15-49 years), of which 6704 were mothers living without human immunodeficiency virus and 1279 were mothers living with human immunodeficiency virus. METHODS: Here, we determined the fertility intentions of mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus using secondary data. Multivariable logistic regression models were used to determine the association of individual and household socio-demographic factors on fertility intentions of mothers living with human immunodeficiency virus and mothers living without human immunodeficiency virus in Zambia. RESULTS: Fertility intention among mothers living with human immunodeficiency virus was 42.1% while that on mothers living without human immunodeficiency virus was 55.5%. Regardless of human immunodeficiency virus status, fertility intention reduced with increasing age. Mothers aged 35-49 years who were living with human immunodeficiency virus (adjusted odds ratio = 0.12, 95% confidence interval = 0.06-0.24) and mothers aged 35-49 years who were living without human immunodeficiency virus (adjusted odds ratio = 0.18, 95% confidence interval = 0.13-0.26) had lower odds of intention to have another child compared to mothers aged 15-24 years. Furthermore, married mothers living with human immunodeficiency virus and those living without human immunodeficiency virus had increased odds of intention of having another child (adjusted odds ratio = 2.52, 95% confidence interval = 1.36-4.66) and (adjusted odds ratio = 3.21, 95% confidence interval = 2.36-4.36), respectively. CONCLUSION: The study has established that age, marital status, parity and employment status were associated with fertility intention among women living with and without human immunodeficiency virus. The results necessitate the need for enhanced maternal health education for mothers regardless of human immunodeficiency virus status. Furthermore, there is a need for continuous counselling for both women living with human immunodeficiency virus and without human immunodeficiency virus during their routine human immunodeficiency virus care, to improve and enhance pregnancy outcomes.

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa.

OBJECTIVE: Various studies have been published to better understand the underlying spatial and temporal dynamics of COVID-19. This review sought to identify different spatial and spatio-temporal modelling methods that have been applied to COVID-19 and examine influential covariates that have been reportedly associated with its risk in Africa. DESIGN: Systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES: Thematically mined keywords were used to identify refereed studies conducted between January 2020 and February 2022 from the following databases: PubMed, Scopus, MEDLINE via Proquest, CINHAL via EBSCOhost and Coronavirus Research Database via ProQuest. A manual search through the reference list of studies was also conducted. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Peer-reviewed studies that demonstrated the application of spatial and temporal approaches to COVID-19 outcomes. DATA EXTRACTION AND SYNTHESIS: A standardised extraction form based on critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist was used to extract the meta-data of the included studies. A validated scoring criterion was used to assess studies based on their methodological relevance and quality. RESULTS: Among 2065 hits in five databases, title and abstract screening yielded 827 studies of which 22 were synthesised and qualitatively analysed. The most common socioeconomic variable was population density. HIV prevalence was the most common epidemiological indicator, while temperature was the most common environmental indicator. Thirteen studies (59%) implemented diverse formulations of spatial and spatio-temporal models incorporating unmeasured factors of COVID-19 and the subtle influence of time and space. Cluster analyses were used across seven studies (32%) to explore COVID-19 variation and determine whether observed patterns were random. CONCLUSION: COVID-19 modelling in Africa is still in its infancy, and a range of spatial and spatio-temporal methods have been employed across diverse settings. Strengthening routine data systems remains critical for generating estimates and understanding factors that drive spatial variation in vulnerable populations and temporal variation in pandemic progression. PROSPERO REGISTRATION NUMBER: CRD42021279767.

Contextual factors and spatial trends of childhood malnutrition in Zambia.

BACKGROUND: Understanding the national burden and epidemiological profile of childhood malnutrition is central to achieving both national and global health priorities. However, national estimates of malnutrition often conceal large geographical disparities. This study examined the prevalence of childhood malnutrition across provinces in Zambia, changes over time, and identified factors associated with the changes. METHODS: We analyzed data from the 2013/4 and 2018 Zambia demographic and health surveys (ZDHS) to examine the spatial heterogeneity and mesoscale correlates of the dual burden of malnutrition in children in Zambia. Maps illustrating the provincial variation of childhood malnutrition were constructed. Socio-demographic and clinical factors associated with childhood malnutrition in 2013 and 2018 were assessed independently using a multivariate logistic model. RESULTS: Between 2013/4 and 2018, the average prevalence of stunting decreased from 40.1% (95% CI: 39.2-40.9) to 34.6% (95% CI:33.6-35.5), wasting decreased from 6.0% (95% CI: 5.6-6.5) to 4.2% (95% CI: 3.8-4.7), underweight decreased from 14.8% (95% CI: 14.1-15.4) to 11.8% (95% CI: 11.2-12.5) and overweight decreased from 5.7% (95% CI: 5.3-6.2) to 5.2% (95% CI: 4.8-5.7). High variability in the prevalence of childhood malnutrition across the provinces were observed. Specifically, stunting and underweight in Northern and Luapula provinces were observed in 2013/14, whereas Lusaka province had a higher degree of variability over the two survey periods. CONCLUSION: The study points to key sub-populations at greater risk and provinces where malnutrition was prevalent in Zambia. Overall, these results have important implications for nutrition policy and program efforts to reduce the double burden of malnutrition in Zambia.

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a review protocol.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that cause coronavirus disease 2019 (COVID-19) have afflicted millions worldwide. Understanding the underlying spatial and temporal dynamics can help orient timely public health policies and optimize the targeting of non-pharmaceutical interventions and vaccines to the most vulnerable populations, particularly in resource-constrained settings. The review systematically summarises important methodological aspects and specificities of spatial approaches applied to COVID-19 in Africa. METHODS: Thematically selected keywords will be used to search for refereed studies in the following electronic databases PubMed, SCOPUS, MEDLINE, CINHAL, and Coronavirus Research Database from January 2020 to February 2022. Two independent reviewers will screen the title, abstracts, and full texts against predefined eligibility criteria based on the study's characteristics, methodological relevance, and quality. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 procedures will be adhered to during the reporting process. DISCUSSION: COVID-19 modeling remains in its infancy, and research is needed to characterize uncertainty and validate various modeling regimes appropriately. It is anticipated that the review will aid spatial, spatio-temporal modeling decisions necessary for mitigating the current and future pandemics. SYSTEMATIC REVIEW REGISTRATION: CRD42021279767.

Health trends, inequalities and opportunities in South Africa's provinces, 1990-2019: findings from the Global Burden of Disease 2019 Study.

BACKGROUND: Over the last 30 years, South Africa has experienced four 'colliding epidemics' of HIV and tuberculosis, chronic illness and mental health, injury and violence, and maternal, neonatal, and child mortality, which have had substantial effects on health and well-being. Using data from the 2019 Global Burden of Diseases, Injuries and Risk Factors Study (GBD 2019), we evaluated national and provincial health trends and progress towards important Sustainable Development Goal targets from 1990 to 2019. METHODS: We analysed GBD 2019 estimates of mortality, non-fatal health loss, summary health measures and risk factor burden, comparing trends over 1990-2007 and 2007-2019. Additionally, we decomposed changes in life expectancy by cause of death and assessed healthcare system performance. RESULTS: Across the nine provinces, inequalities in mortality and life expectancy increased over 1990-2007, largely due to differences in HIV/AIDS, then decreased over 2007-2019. Demographic change and increases in non-communicable diseases nearly doubled the number of years lived with disability between 1990 and 2019. From 1990 to 2019, risk factor burdens generally shifted from communicable and nutritional disease risks to non-communicable disease and injury risks; unsafe sex remained the top risk factor. Despite widespread improvements in healthcare system performance, the greatest gains were generally in economically advantaged provinces. CONCLUSIONS: Reductions in HIV/AIDS and related conditions have led to improved health since 2007, though most provinces still lag in key areas. To achieve health targets, provincial governments should enhance health investments and exchange of knowledge, resources and best practices alongside populations that have been left behind, especially following the COVID-19 pandemic.

Joint spatio-temporal modelling of adverse pregnancy outcomes sharing common risk factors at sub-county level in Kenya, 2016-2019.

BACKGROUND: Adverse pregnancy outcomes jointly account for a high proportion of mortality and morbidity among pregnant women and their infants. Furthermore, the burden attributed to adverse pregnancy outcomes remains high and inadequately characterised due to the intricate interplay of its etiology and shared set of important risk factors. This study sought to quantify and map the underlying risk of multiple adverse pregnancy outcomes in Kenya at sub-county level using a shared component space-time modelling framework. METHODS: Reported sub-county level adverse pregnancy outcomes count from January 2016 - December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical spatio-temporal model was used to estimate the joint burden of adverse pregnancy outcomes in space (sub-county) and time (year). To improve the precision of our estimates over time and space, information across the outcomes were combined via the shared and the outcome-specific components using a shared component model with spatio-temporal interactions. RESULTS: Overall, the total number of adverse outcomes in pregnancy increased by 14.2% (95% UI: 14.0-14.5) from 88,816 cases in 2016 to 101,455 cases in 2019. Between 2016 and 2019, the estimated low birth weight rate and the pre-term birth rate were 4.5 (95% UI: 4.4-4.7) and 2.3 (95% UI: 2.2-2.5) per 100 live births. The stillbirth and neonatal death rates were estimated to be 18.7 (95% UI: 18.0-19.4) and 6.9 (95% UI: 6.4-7.4) per 1000 live births. The magnitude of the spatio-temporal variation attributed to shared risk was high for pre-term births, low birth weight, neonatal deaths, stillbirths and neonatal deaths, respectively. The shared risk patterns were dominant in sub-counties located along the Indian ocean coastline, central and western Kenya. CONCLUSIONS: This study demonstrates the usefulness of a Bayesian joint spatio-temporal shared component model in exploiting specific and shared risk of adverse pregnancy outcomes sub-nationally. By identifying sub-counties with elevated risks and data gaps, our estimates not only assert the need for bolstering maternal health programs in the identified high-risk sub-counties but also provides a baseline against which to assess the progress towards the attainment of Sustainable Development Goals.

Mapping of anaemia prevalence among pregnant women in Kenya (2016-2019).

BACKGROUND: Reducing the burden of anaemia is a critical global health priority that could improve maternal outcomes amongst pregnant women and their neonates. As more counties in Kenya commit to universal health coverage, there is a growing need for optimal allocation of the limited resources to sustain the gains achieved with the devolution of healthcare services. This study aimed to describe the spatio-temporal patterns of maternal anaemia prevalence in Kenya from 2016 to 2019. METHODS: Quarterly reported sub-county level maternal anaemia cases from January 2016 - December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical negative binomial spatio-temporal conditional autoregressive (CAR) model was used to estimate maternal anaemia prevalence by sub-county and quarter. Spatial and temporal correlations were considered by assuming a conditional autoregressive and a first-order autoregressive process on sub-county and seasonal specific random effects, respectively. RESULTS: The overall estimated number of pregnant women with anaemia increased by 90.1% (95% uncertainty interval [95% UI], 89.9-90.2) from 155,539 cases in 2016 to 295,642 cases 2019. Based on the WHO classification criteria, the proportion of sub-counties with normal prevalence decreased from 28.0% (95% UI, 25.4-30.7) in 2016 to 5.4% (95% UI, 4.1-6.7) in 2019, whereas moderate anaemia prevalence increased from 16.8% (95% UI, 14.7-19.1) in 2016 to 30.1% (95% UI, 27.5-32.8) in 2019 and severe anaemia prevalence increased from 7.0% (95% UI, 5.6-8.6) in 2016 to 16.6% (95% UI, 14.5-18.9) in 2019. Overall, 45.1% (95% UI: 45.0-45.2) of the estimated cases were in malaria-endemic sub-counties, with the coastal endemic zone having the highest proportion 72.8% (95% UI: 68.3-77.4) of sub-counties with severe prevalence. CONCLUSION: As the number of women of reproductive age continues to grow in Kenya, the use of routinely collected data for accurate mapping of poor maternal outcomes remains an integral component of a functional maternal health strategy. By unmasking the sub-county disparities often concealed by national and county estimates, our study findings reiterate the importance of maternal anaemia prevalence as a metric for estimating malaria burden and offers compelling policy implications for achieving national nutritional targets.

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.

Spatio - temporal modelling assessing the burden of malaria in affected low and middle-income countries: a scoping review.

INTRODUCTION: Spatio - temporal modelling of malaria has proven to be a valuable tool for forecasting as well as control and elimination activities. This has been triggered by an increasing availability of spatially indexed data, enabling not only the characterisation of malaria at macrospatial and microspatial levels but also the development of geospatial techniques and tools that enable health policy planners to use these available data more effectively. However, there has been little synthesis regarding the variety of spatio - temporal approaches employed, covariates employed and 'best practice' type recommendations to guide future modelling decisions. This review will seek to summarise available evidence on the current state of spatio - temporal modelling approaches that have been employed in malaria modelling in low and middle-income countries within malaria transmission limits, so as to guide future modelling decisions. METHODS AND ANALYSIS: A comprehensive search for articles published from January 1968 to April 2018 will be conducted using of the following electronic databases: PubMed, Web of Science, JSTOR, Cochrane CENTRAL via Wiley, Academic Search Complete via EBSCOhost, MasterFILE Premier via EBSCOhost, CINAHL via EBSCOhost, MEDLINE via EBSCOhost and Google Scholar. Relevant grey literature sources such as unpublished reports, conference proceedings and dissertations will also be incorporated in the search. Two reviewers will independently conduct the title screening, abstract screening and, thereafter, a full-text review of all potentially eligible articles. Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols guidelines will be used as the standard reporting format. A qualitative thematic analysis will be used to group and evaluate selected studies around their aim, spatio - temporal methodology employed, covariates used and model validation techniques. ETHICS AND DISSEMINATION: Ethical approval is not applicable to this study. The results will be disseminated through a peer-reviewed journal and presented in conferences related to malaria and spatial epidemiology. PROSPERO REGISTRATION NUMBER: CRD42017076427.