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.

Changing malaria fever test positivity among paediatric admissions to Tororo district hospital, Uganda 2012-2019.

BACKGROUND: The World Health Organization (WHO) promotes long-lasting insecticidal nets (LLIN) and indoor residual house-spraying (IRS) for malaria control in endemic countries. However, long-term impact data of vector control interventions is rarely measured empirically. METHODS: Surveillance data was collected from paediatric admissions at Tororo district hospital for the period January 2012 to December 2019, during which LLIN and IRS campaigns were implemented in the district. Malaria test positivity rate (TPR) among febrile admissions aged 1 month to 14 years was aggregated at baseline and three intervention periods (first LLIN campaign; Bendiocarb IRS; and Actellic IRS + second LLIN campaign) and compared using before-and-after analysis. Interrupted time-series analysis (ITSA) was used to determine the effect of IRS (Bendiocarb + Actellic) with the second LLIN campaign on monthly TPR compared to the combined baseline and first LLIN campaign periods controlling for age, rainfall, type of malaria test performed. The mean and median ages were examined between intervention intervals and as trend since January 2012. RESULTS: Among 28,049 febrile admissions between January 2012 and December 2019, TPR decreased from 60% at baseline (January 2012-October 2013) to 31% during the final period of Actellic IRS and LLIN (June 2016-December 2019). Comparing intervention intervals to the baseline TPR (60.3%), TPR was higher during the first LLIN period (67.3%, difference 7.0%; 95% CI 5.2%, 8.8%, p < 0.001), and lower during the Bendiocarb IRS (43.5%, difference - 16.8%; 95% CI - 18.7%, - 14.9%) and Actellic IRS (31.3%, difference - 29.0%; 95% CI - 30.3%, - 27.6%, p < 0.001) periods. ITSA confirmed a significant decrease in the level and trend of TPR during the IRS (Bendicarb + Actellic) with the second LLIN period compared to the pre-IRS (baseline + first LLIN) period. The age of children with positive test results significantly increased with time from a mean of 24 months at baseline to 39 months during the final IRS and LLIN period. CONCLUSION: IRS can have a dramatic impact on hospital paediatric admissions harbouring malaria infection. The sustained expansion of effective vector control leads to an increase in the age of malaria positive febrile paediatric admissions. However, despite large reductions, malaria test-positive admissions continued to be concentrated in children aged under five years. Despite high coverage of IRS and LLIN, these vector control measures failed to interrupt transmission in Tororo district. Using simple, cost-effective hospital surveillance, it is possible to monitor the public health impacts of IRS in combination with LLIN.

Insecticide-treated net distribution in Western Kenya: impacts related to COVID-19 and health worker strikes.

We examined the impact of coronavirus disease (COVID) mitigation, supply and distribution interruptions on the delivery of long-lasting insecticide-treated nets (LLINs) in Western Kenya. The median monthly distribution of LLINs declined during COVID mitigation strategies (March-July 2020) and during the health worker strikes (December 2020-February 2021). Recovery periods followed initial declines, indicative of a 'catching up' on missed routine distribution. Mass community campaigns were delayed by 10 months. These observations offer encouragement for routine net distribution resilience, but complete interruptions of planned mass distributions require alternate strategies during pandemics.

Geographic accessibility to public and private health facilities in Kenya in 2021: An updated geocoded inventory and spatial analysis.

Objectives: To achieve universal health coverage, adequate geographic access to quality healthcare services is vital and should be characterized periodically to support planning. However, in Kenya, previous assessments of geographic accessibility have relied on public health facility lists only, assembled several years ago. Here, for the first time we assemble a geocoded list of public and private health facilities in 2021 and make use of this updated list to interrogate geographical accessibility to all health providers. Methods: Existing health provider lists in Kenya were accessed, merged, cleaned, harmonized, and assigned a unique geospatial location. The resultant master list was combined with road network, land use, topography, travel barriers and healthcare-seeking behavior within a geospatial framework to estimate travel time to the nearest (i) private, (ii) public, and (iii) both (public and private-PP) health facilities through a travel scenario involving walking, bicycling and motorized transport. The proportion of the population within 1 h and outside 2-h was computed at 300 × 300 spatial resolution and aggregated at subnational units used for decision-making. Areas with a high disease prevalence for common infections that were outside 1-h catchment (dual burden) were also identified to guide prioritization. Results: The combined database contained 13,579 health facilities, both in the public (55.5%) and private-for-profit sector (44.5%) in 2021. The private health facilities' distribution was skewed toward the urban counties. Nationally, average travel time to the nearest health facility was 130, 254, and 128 min while the population within 1-h was 89.4, 80.5, and 89.6% for the public, private and PP health facility, respectively. The population outside 2-h were 6% for public and PP and 11% for the private sector. Mean travel time across counties was heterogeneous, while the population within 1-h ranged between 38 and 100% in both the public sector and PP. Counties in northwest and southeast Kenya had a dual burden. Conclusion: Continuous updating and geocoding of health facilities will facilitate an improved understanding of healthcare gaps for planning. Heterogeneities in geographical access continue to persist, with some areas having a dual burden and should be prioritized toward reducing health inequities and attaining universal health coverage.