Healthcare-seeking behavior for respiratory illnesses in Kenya: implications for burden of disease estimation.

BACKGROUND: Understanding healthcare-seeking patterns for respiratory illness can help improve estimation of disease burden and target public health interventions to control acute respiratory disease in Kenya. METHODS: We conducted a cross-sectional survey to determine healthcare utilization patterns for acute respiratory illness (ARI) and severe pneumonia in four diverse counties representing urban, peri-urban, rural mixed farmers, and rural pastoralist communities in Kenya using a two-stage (sub-locations then households) cluster sampling procedure. Healthcare seeking behavior for ARI episodes in the last 14 days, and severe pneumonia in the last 12 months was evaluated. Severe pneumonia was defined as reported cough and difficulty breathing for > 2 days and report of hospitalization or recommendation for hospitalization, or a danger sign (unable to breastfeed/drink, vomiting everything, convulsions, unconscious) for children < 5 years, or report of inability to perform routine chores. RESULTS: From August through September 2018, we interviewed 28,072 individuals from 5,407 households. Of those surveyed, 9.2% (95% Confidence Interval [CI] 7.9-10.7) reported an episode of ARI, and 4.2% (95% CI 3.8-4.6) reported an episode of severe pneumonia. Of the reported ARI cases, 40.0% (95% CI 36.8-43.3) sought care at a health facility. Of the74.2% (95% CI 70.2-77.9) who reported severe pneumonia and visited a medical health facility, 28.9% (95% CI 25.6-32.6) were hospitalized and 7.0% (95% CI 5.4-9.1) were referred by a clinician to the hospital but not hospitalized. 21% (95% CI 18.2-23.6) of self-reported severe pneumonias were hospitalized. Children aged < 5 years and persons in households with a higher socio-economic status were more likely to seek care for respiratory illness at a health facility. CONCLUSION: Our findings suggest that hospital-based surveillance captures less than one quarter of severe pneumonia in the community. Multipliers from community household surveys can account for underutilization of healthcare resources and under-ascertainment of severe pneumonia at hospitals.

Temporal variation in confirmed diagnosis of fever-related malarial cases among children under-5 years by community health workers and in health facilities between years 2013 and 2015 in Siaya County, Kenya.

BACKGROUND: Malaria case management continues to experience dynamic changes. Building community capacity is instrumental in both prevention and treatment of malaria. The World Health Organization (WHO) recommends utilization of well-trained and supervised community health workers (CHWs) to reduce the burden of malaria deaths among children under-5 years of age in Africa. Longitudinally-tracked information on utilization of CHWs by communities in terms of trends in diagnosis of malaria in children under-5 years of age is essential in influencing national and local malaria control policies and strategies. METHODS: A desktop review was carried out of a database consisting of confirmed uncomplicated malaria cases in 10 villages using CHWs and out-patient departments of 10 health facilities in children under-five for the period of 3 years between January 2013 and December 2015. Analyses of association between the diagnosed cases and satellite-based rainfall, village and time (months and years) were carried out using a Poisson regression model. RESULTS: Analysis of malaria diagnoses made by CHWs showed the following trends: (i) the incidence of reported documented malaria-positive fever cases increased with time (2013-2015) and the difference over the years was statistically significant (P < 0.001), (ii) specific village was significantly associated (P < 0.001) with reporting malaria-positive fever cases, (iii) the long-term monthly sequence starting from highest to lowest incidence of reported malaria-positive fever cases was July, May and June, March, August, April, September, November, and February, October and, finally, January, and the difference in reported malaria-positives between the months was statistically significant (P = 0.001) and (iv) none of the tested rainfall regimes (current, lagged or cumulative) was associated with reported malaria-positive fever cases during the 3-year period (P > 0.1). Looking at the number of diagnoses made at the health facilities, (i) The number of reported malaria-positive fever cases decreased with time (2013-2015) and the difference among the years was not statistically significant (P = 0.399), (ii) The long-term monthly sequence starting from highest to lowest number of reported malaria-positive fever cases was July, June, May, April, January, August, March, February, September, November, October and December, and the difference between the months was statistically significant (P < 0.001). CONCLUSIONS: CHWs have the potential to play a major role in diagnosing and treating malaria, thereby decreasing under-five children mortality. Temporally, the risk of diagnosing malaria seems predictable and this may present opportunities for policy-targeted malaria preparedness and control. The findings are expected to support policy actions that may scale-up community health services in remote rural settings.