INTRODUCTION: High blood pressure is recognized as a leading risk factor for stroke and death in sub-Saharan Africa (sSA). While many studies have examined the role of established risk factors such as obesity and salt consumption, less is known about other factors, such as infection, that could be of particular importance in sSA. Ambulatory blood pressure measurement has emerged as the optimal method in recent years in Western settings, but there has been limited use to date in sSA. This work presents the results of a study investigating whether malaria, which is widespread in sSA could contribute to the development of high blood pressure using ambulatory measurements. METHODS: Preliminary work involved determining the prevalence of hypertension in Kilifi, Kenya and examining the population-level effects of using ambulatory blood pressure monitoring (ABPM) for diagnosing hypertension. A literature review outlining the basis of the malaria-high blood pressure hypothesis and the Mendelian randomization method for testing the hypothesis was conducted. Sickle cell trait and alpha (+) thalassemia were chosen as instrumental variables to represent malaria exposure because they protect against malaria. Two studies were performed in Nairobi, Kenya among the same cohort to confirm that sickle-cell trait and alpha-thalassemia do not influence blood pressure in the absence of malaria and were therefore valid instrumental variables to test the malaria-high blood pressure hypothesis in Kilifi where there is malaria transmission. A Mendelian randomization study was then conducted in Kilifi, Kenya where 24-hour blood pressure and arterial stiffness indices were compared in individuals with and without sickle cell trait and alpha thalassemia. RESULTS: The prevalence of hypertension in Kilifi, a rural area, was found to be as high as in urban areas of Kenya despite the low frequency of classical risk factors such as obesity and excessive salt consumption. Use of ambulatory blood pressure monitoring for diagnosing hypertension was found to improve the accuracy of detection of high blood pressure. Neither Sickle-cell trait (SCT) nor alpha+ thalassemia influenced blood pressure or arterial stiffness indices among adolescents that had been lifelong residents of Nairobi, where there is no malaria transmission. Among individuals that had been lifelong residents of Kilifi, Kenya where there has been on-going malaria transmission, blood pressure was found to be lower among individuals with SCT, which protects against malaria episodes compared to those without SCT. The difference in BP by SCT status was larger in women than in men. There were no significant differences in arterial stiffness based on SCT status. CONCLUSION: This work suggests that malaria contributes to the burden of hypertension in sSA, and the control of malaria may lead to a reduction in blood pressure in this group. Future work should focus on confirming the findings using alternative study designs such as examining blood pressure in cohorts born before and after complete malaria elimination in parts of the world where this has been achieved. Subsequent work would involve delineating the pathophysiological mechanisms involved in malaria induced BP elevation with a view to generating new drugs to control hypertension.

Summary In this paper, we set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to provide a tutorial guide that can be used in order to identify parsimonious geostatistical models for prevalence mapping. A general variogram-based Monte Carlo procedure is proposed to check the validity of the modelling assumptions. We describe and contrast likelihood-based and Bayesian methods of inference, showing how to account for parameter uncertainty under each of the two paradigms. We also describe extensions of the standard model for disease prevalence that can be used when stationarity of the spatio-temporal covariance function is not supported by the data. We discuss how to define predictive targets and argue that exceedance probabilities provide one of the most effective ways to convey uncertainty in prevalence estimates. We describe statistical software for the visualisation of spatio-temporal predictive summaries of prevalence through interactive animations. Finally, we illustrate an application to historical malaria prevalence data from 1 334 surveys conducted in Senegal between 1905 and 2014.

ABSTRACT Nature Snow, Robert W., Guerra, Carlos A., Noor, Abdisalan M., Myint, Hly Y., Hay, Simon I. Pages:E4-E5, Volume:437, Edition:, Date, Link: http://hinari-gw.who.int/whalecomdx.doi.org/whalecom0/10.1038/nature04180 Notes:10.1038/nature04180 ISBN: 0028-0836 Permanent ID: Accession Number: Author Address: STATISTICS

Reestablishing exclusive breastfeeding is the cornerstone of the 2013 World Health Organization (WHO) treatment guidelines for acute malnutrition in infants less than 6 months. However, no studies have investigated guideline implementation and subsequent outcomes in a public hospital setting in Africa. To facilitate implementation of the WHO 2013 guidelines in Kilifi County Hospital, Kenya, we developed standard operating procedure, recruited, and trained three breastfeeding peer supporters (BFPS). Between September 2016 and January 2018, the BFPS provided individual breastfeeding support to mothers of infants aged 4 weeks to 4 months admitted to Kilifi County Hospital with an illness and acute malnutrition (mid-upper-arm circumference < 11.0 cm OR weight-for-age z score < -2 OR weight-for-length z score < -2). Infants were followed daily while in hospital then every 2 weeks for 6 weeks after discharge with data collected on breastfeeding, infant growth, morbidity, and mortality. Of 106 infants with acute malnutrition at admission, 51 met the inclusion criteria for the study. Most enrolled mothers had multiple breastfeeding challenges, which were predominantly technique based. Exclusive breastfeeding was 55% at admission and 81% at discharge; at discharge 67% of infants had attained a weight velocity of >5 g/kg/day for three consecutive days on breastmilk alone. Gains in weight-for-length z score and weight-for-age z score were generally not sustained beyond 2 weeks after discharge. BFPS operated effectively in an inpatient setting, applying the 2013 updated WHO guidelines and increasing rates of exclusive breastfeeding at discharge. However, lack of continued increase in anthropometric Z scores after discharge suggests the need for more sustained interventions.

Summary In this paper, we set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to provide a tutorial guide that can be used in order to identify parsimonious geostatistical models for prevalence mapping. A general variogram-based Monte Carlo procedure is proposed to check the validity of the modelling assumptions. We describe and contrast likelihood-based and Bayesian methods of inference, showing how to account for parameter uncertainty under each of the two paradigms. We also describe extensions of the standard model for disease prevalence that can be used when stationarity of the spatio-temporal covariance function is not supported by the data. We discuss how to define predictive targets and argue that exceedance probabilities provide one of the most effective ways to convey uncertainty in prevalence estimates. We describe statistical software for the visualisation of spatio-temporal predictive summaries of prevalence through interactive animations. Finally, we illustrate an application to historical malaria prevalence data from 1 334 surveys conducted in Senegal between 1905 and 2014.

ABSTRACT Nature Snow, Robert W., Guerra, Carlos A., Noor, Abdisalan M., Myint, Hly Y., Hay, Simon I. Pages:E4-E5, Volume:437, Edition:, Date, Link: http://hinari-gw.who.int/whalecomdx.doi.org/whalecom0/10.1038/nature04180 Notes:10.1038/nature04180 ISBN: 0028-0836 Permanent ID: Accession Number: Author Address: STATISTICS

INTRODUCTION: Amid the rising number of people with non-communicable diseases (NCDs), Kenya has invested in strengthening primary care and in efforts to expand existing service delivery platforms to integrate NCD care. One such approach is the AMPATH (Academic Model Providing Access to Healthcare) model in western Kenya, which provides the platform for the Primary Health Integrated Care Project for Chronic Conditions (PIC4C), launched in 2018 to further strengthen primary care services for the prevention and control of hypertension, diabetes, breast and cervical cancer. This study seeks to understand how well PIC4C delivers on its intended aims and to inform and support scale up of the PIC4C model for integrated care for people with NCDs in Kenya. METHODS AND ANALYSIS: The study is guided by a conceptual framework on implementing, sustaining and spreading innovation in health service delivery. We use a multimethod design combining qualitative and quantitative approaches, involving: (1) in-depth interviews with health workers and decision-makers to explore experiences of delivering PIC4C; (2) a cross-sectional survey of patients with diabetes or hypertension and in-depth interviews to understand how well PIC4C meets patients’ needs; (3) a cohort study with an interrupted time series analysis to evaluate the degree to which PIC4C leads to health benefits such as improved management of hypertension or diabetes; and (4) a cohort study of households to examine the extent to which the national hospital insurance chronic care package provides financial risk protection to people with hypertension or diabetes within PIC4C. ETHICS AND DISSEMINATION: The study has received approvals from Moi University Institutional Research and Ethics Committee (FAN:0003586) and the London School of Hygiene & Tropical Medicine (17940). Workshops with key stakeholders at local, county, national and international levels will ensure early and wide dissemination of our findings to inform scale up of this model of care. We will also publish findings in peer-reviewed journals.

BACKGROUND: Sub-Saharan Africa (SSA) has the highest age-adjusted burden of hypertension and cardiovascular disease (CVD). SSA also experiences many viral infections due to unique environmental and societal factors. The purpose of this narrative review is to examine evidence around how hypertension, CVD, and emerging viral infections interact in SSA. METHODS: In September 2021, we conducted a search in MEDLINE, Embase, and Scopus, limited to English language studies published since 1990, and found a total of 1169 articles. Forty-seven original studies were included, with 32 on COVID-19 and 15 on other emerging viruses. RESULTS: Seven articles, including those with the largest sample size and most robust study design, found an association between preexisting hypertension or CVD and COVID-19 severity or death. Ten smaller studies found no association, and 17 did not calculate statistics to compare groups. Two studies assessed the impact of COVID-19 on incident CVD, with one finding an increase in stroke admissions. For other emerging viruses, 3 studies did not find an association between preexisting hypertension or CVD on West Nile and Lassa fever mortality. Twelve studies examined other emerging viral infections and incident CVD, with 4 finding no association and 8 not calculating statistics. CONCLUSIONS: Growing evidence from COVID-19 suggests viruses, hypertension, and CVD interact on multiple levels in SSA, but research gaps remain especially for other emerging viral infections. SSA can and must play a leading role in the study and control of emerging viral infections, with expansion of research and public health infrastructure to address these interactions.

COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 – 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 – 16.74) – 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 – 36.96) – 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.

Severely ill children in low- and middle-income countries (LMICs) experience high rates of mortality from a broad range of infectious diseases, with the risk of infection-related death compounded by co-existing undernutrition. How undernutrition and acute illness impact immune responses in young children in LMICs remains understudied, and it is unclear what aspects of immunity are compromised in this highly vulnerable population. To address this knowledge gap, we profiled longitudinal whole blood cytokine responses to Toll-like receptor (TLR) ligands among severely ill children (n=63; 2-23 months old) with varied nutritional backgrounds, enrolled in the CHAIN Network cohort from Kampala, Uganda, and Kilifi, Kenya, and compared these responses to similar-aged well children in local communities (n=41). Cytokine responses to ligands for TLR-4 and TLR-7/8, as well as Staphylococcus enterotoxin B (SEB), demonstrated transient impairment in T cell function among acutely ill children, whereas innate cytokine responses were exaggerated during both acute illness and following clinical recovery. Nutritional status was associated with the magnitude of cytokine responses in all stimulated conditions. Among children who died following hospital discharge or required hospital re-admission, exaggerated production of interleukin-7 (IL-7) to all stimulation conditions, as well as leukopenia with reduced lymphocyte and monocyte counts, were observed. Overall, our findings demonstrate exaggerated innate immune responses to pathogen-associated molecules among acutely ill young children that persist during recovery. Heightened innate immune responses to TLR ligands may contribute to chronic systemic inflammation and dysregulated responses to subsequent infectious challenges. Further delineating mechanisms of innate immune dysregulation in this population should be prioritized to identify novel interventions that promote immune homeostasis and improve outcomes.