Malaria vaccine coverage estimation using age-eligible populations and service user denominators in Kenya

Background The World Health Organization approved the RTS,S/AS01 malaria vaccine for wider rollout, and Kenya participated in a phased pilot implementation from 2019 to understand its impact under routine conditions. Vaccine delivery requires coverage measures at national and sub-national levels to evaluate progress over time. This study aimed to estimate the coverage of the RTS,S/AS01 vaccine during the first 36 months of the Kenyan pilot implementation. Methods Monthly dose-specific immunization data for 23 sub-counties were obtained from routine health information systems at the facility level for 2019–2022. Coverage of each RTS,S/AS01 dose was determined using reported doses as a numerator and service-based (Penta 1 and Measles) or population (projected infant populations from WorldPop) as denominators. Descriptive statistics of vaccine delivery, dropout rates and coverage estimates were computed across the 36-month implementation period. Results Over 36 months, 818,648 RTSS/AS01 doses were administered. Facilities managed by the Ministry of Health and faith-based organizations accounted for over 88% of all vaccines delivered. Overall, service-based malaria vaccine coverage was 96%, 87%, 78%, and 39% for doses 1–4 respectively. Using a population-derived denominator for age-eligible children, vaccine coverage was 78%, 68%, 57%, and 24% for doses 1–4, respectively. Of the children that received measles dose 1 vaccines delivered at 9 months (coverage: 95%), 82% received RTSS/AS01 dose 3, only 66% of children who received measles dose 2 at 18 months (coverage: 59%) also received dose 4. Conclusion The implementation programme successfully maintained high levels of coverage for the first three doses of RTSS/AS01 among children defined as EPI service users up to 9 months of age but had much lower coverage within the community with up to 1 in 5 children not receiving the vaccine. Consistent with vaccines delivered over the age of 1 year, coverage of the fourth malaria dose was low. Vaccine uptake, service access and dropout rates for malaria vaccines require constant monitoring and intervention to ensure maximum protection is conferred

Geographic accessibility and hospital competition for emergency blood transfusion services in Bungoma, Western Kenya

Background Estimating accessibility gaps to essential health interventions helps to allocate and prioritize health resources. Access to blood transfusion represents an important emergency health requirement. Here, we develop geo-spatial models of accessibility and competition to blood transfusion services in Bungoma County, Western Kenya. Methods Hospitals providing blood transfusion services in Bungoma were identified from an up-dated geo-coded facility database. AccessMod was used to define care-seeker’s travel times to the nearest blood transfusion service. A spatial accessibility index for each enumeration area (EA) was defined using modelled travel time, population demand, and supply available at the hospital, assuming a uniform risk of emergency occurrence in the county. To identify populations marginalized from transfusion services, the number of people outside 1-h travel time and those residing in EAs with low accessibility indexes were computed at the sub-county level. Competition between the transfusing hospitals was estimated using a spatial competition index which provided a measure of the level of attractiveness of each hospital. To understand whether highly competitive facilities had better capacity for blood transfusion services, a correlation test between the computed competition metric and the blood units received and transfused at the hospital was done. Results 15 hospitals in Bungoma county provide transfusion services, however these are unevenly distributed across the sub-counties. Average travel time to a blood transfusion centre in the county was 33 min and 5% of the population resided outside 1-h travel time. Based on the accessibility index, 38% of the EAs were classified to have low accessibility, representing 34% of the population, with one sub-county having the highest marginalized population. The computed competition index showed that hospitals in the urban areas had a spatial competitive advantage over those in rural areas. Conclusion The modelled spatial accessibility has provided an improved understanding of health care gaps essential for health planning. Hospital competition has been illustrated to have some degree of influence in provision of health services hence should be considered as a significant external factor impacting the delivery, and re-design of available services

Malaria vaccine coverage estimation using age-eligible populations and service user denominators in Kenya

Abstract Background The World Health Organization approved the RTS,S/AS01 malaria vaccine for wider rollout, and Kenya participated in a phased pilot implementation from 2019 to understand its impact under routine conditions. Vaccine delivery requires coverage measures at national and sub-national levels to evaluate progress over time. This study aimed to estimate the coverage of the RTS,S/AS01 vaccine during the first 36 months of the Kenyan pilot implementation. Methods Monthly dose-specific immunization data for 23 sub-counties were obtained from routine health information systems at the facility level for 2019–2022. Coverage of each RTS,S/AS01 dose was determined using reported doses as a numerator and service-based (Penta 1 and Measles) or population (projected infant populations from WorldPop) as denominators. Descriptive statistics of vaccine delivery, dropout rates and coverage estimates were computed across the 36-month implementation period. Results Over 36 months, 818,648 RTSS/AS01 doses were administered. Facilities managed by the Ministry of Health and faith-based organizations accounted for over 88% of all vaccines delivered. Overall, service-based malaria vaccine coverage was 96%, 87%, 78%, and 39% for doses 1–4 respectively. Using a population-derived denominator for age-eligible children, vaccine coverage was 78%, 68%, 57%, and 24% for doses 1–4, respectively. Of the children that received measles dose 1 vaccines delivered at 9 months (coverage: 95%), 82% received RTSS/AS01 dose 3, only 66% of children who received measles dose 2 at 18 months (coverage: 59%) also received dose 4. Conclusion The implementation programme successfully maintained high levels of coverage for the first three doses of RTSS/AS01 among children defined as EPI service users up to 9 months of age but had much lower coverage within the community with up to 1 in 5 children not receiving the vaccine. Consistent with vaccines delivered over the age of 1 year, coverage of the fourth malaria dose was low. Vaccine uptake, service access and dropout rates for malaria vaccines require constant monitoring and intervention to ensure maximum protection is conferred

Additional file 1 of Malaria vaccine coverage estimation using age-eligible populations and service user denominators in Kenya

Additional file 1: Table S1. Kenya national Extended Programme for Immunisation (EPI) vaccine schedule. Figure S1. Flowchart of the selection process to determine facilities routinely offering vaccination services in RTS, S/AS01 intervention areas (23 sub-counties) from DHIS2 listing. Figure S2. Gantt chart illustration of numerator and denominator counts used for coverage computation. Figure S3. Annual population density maps of children under 1 year within RTS,S/AS01 implementation sub-counties for the years 2019-2022. Table S2. Characteristics of 537 vaccinating facilities within the 23 implementation sub-counties. Figure S4. Animation of cumulative Penta 1 and RTS,S/AS01 vaccines administered at facility level from September 2019 to August 2022 (N = 537). Figure S5. Chart showing sub-county coverage rankings of RTS,S/AS01 vaccine doses for each denominator

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran

Maternal and neonatal outcomes after caesarean delivery in the African Surgical Outcomes Study: a 7-day prospective observational cohort study.

BACKGROUND: Maternal and neonatal mortality is high in Africa, but few large, prospective studies have been done to investigate the risk factors associated with these poor maternal and neonatal outcomes. METHODS: A 7-day, international, prospective, observational cohort study was done in patients having caesarean delivery in 183 hospitals across 22 countries in Africa. The inclusion criteria were all consecutive patients (aged ≥18 years) admitted to participating centres having elective and non-elective caesarean delivery during the 7-day study cohort period. To ensure a representative sample, each hospital had to provide data for 90% of the eligible patients during the recruitment week. The primary outcome was in-hospital maternal mortality and complications, which were assessed by local investigators. The study was registered on the South African National Health Research Database, number KZ_2015RP7_22, and on ClinicalTrials.gov, number NCT03044899. FINDINGS: Between February, 2016, and May, 2016, 3792 patients were recruited from hospitals across Africa. 3685 were included in the postoperative complications analysis (107 missing data) and 3684 were included in the maternal mortality analysis (108 missing data). These hospitals had a combined number of specialist surgeons, obstetricians, and anaesthetists totalling 0·7 per 100 000 population (IQR 0·2-2·0). Maternal mortality was 20 (0·5%) of 3684 patients (95% CI 0·3-0·8). Complications occurred in 633 (17·4%) of 3636 mothers (16·2-18·6), which were predominantly severe intraoperative and postoperative bleeding (136 [3·8%] of 3612 mothers). Maternal mortality was independently associated with a preoperative presentation of placenta praevia, placental abruption, ruptured uterus, antepartum haemorrhage (odds ratio 4·47 [95% CI 1·46-13·65]), and perioperative severe obstetric haemorrhage (5·87 [1·99-17·34]) or anaesthesia complications (11·47 (1·20-109·20]). Neonatal mortality was 153 (4·4%) of 3506 infants (95% CI 3·7-5·0). INTERPRETATION: Maternal mortality after caesarean delivery in Africa is 50 times higher than that of high-income countries and is driven by peripartum haemorrhage and anaesthesia complications. Neonatal mortality is double the global average. Early identification and appropriate management of mothers at risk of peripartum haemorrhage might improve maternal and neonatal outcomes in Africa. FUNDING: Medical Research Council of South Africa.Medical Research Council of South Africa