Geospatial mapping of timely access to inpatient neonatal care and its relationship to neonatal mortality in Kenya

Globally, 2.4 million newborns die in the first month of life, with neonatal mortality rates (NMR) per 1,000 livebirths being highest in sub-Saharan Africa. Improving access to inpatient newborn care is necessary for reduction of neonatal deaths in the region. We explore the relationship between distance to inpatient hospital newborn care and neonatal mortality in Kenya. Data on service availability from numerous sources were used to map hospitals that care for newborns with very low birth weight (VLBW). Estimates of livebirths needing VLBW services were mapped from population census data at 100 m spatial resolution using a random forest algorithm and adjustments using a systematic review of livebirths needing these services. A cost distance algorithm that adjusted for proximity to roads, road speeds, land use and protected areas was used to define geographic access to hospitals offering VLBW services. County-level access metrics were then regressed against estimates of NMR to assess the contribution of geographic access to VLBW services on newborn deaths while controlling for wealth, maternal education and health workforce. 228 VLBW hospitals were mapped, with 29,729 births predicted as requiring VLBW services in 2019. Approximately 80.3% of these births were within 2 hours of the nearest VLBW hospital. Geographic access to these hospitals, ranged from less than 30% in Wajir and Turkana to as high as 80% in six counties. Regression analysis showed that a one percent increase in population within 2 hours of a VLBW hospital was associated with a reduction of NMR by 0.24. Despite access in the country being above the 80% threshold, 17/47 counties do not achieve this benchmark. To reduce inequities in NMR in Kenya, policies to improve care must reduce geographic barriers to access and progressively improve facilities' capacity to provide quality care for VLBW newborns.

Unmet need for COVID-19 vaccination coverage in Kenya

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.