Coronavirus disease 2019 risk assessment of adults and geospatial mapping in selected communities of Southwest Nigeria.

Background: Coronavirus disease 2019 (COVID-19) remained a worldwide public health problem. Risk assessment and mapping can be deployed to assist in the control and management of disease outbreaks. Aim: The aim of this study was to conduct COVID-19 risk assessment and mapping in selected communities of Southwest Nigeria. Methods: This was a cross-sectional study of adults, 18 years and above, involving the use of multi-stage sampling. Data collection was done with a pre-tested, structured, interviewer-administered questionnaire. The Statistical Package for the Social Sciences version 23 and Environmental Systems Research Institute ArcGIS desktop version 10.5 were used for data analysis and spatial mapping, respectively. The threshold for statistical significance was set at P < 0.05. Results: The respondents' mean age was 40.6 ± 14.5 years. Self-reported vulnerability factors identified included hypertension, diabetes mellitus, working in hospital facility, cigarette smoking and age ≥60 years amongst others. About a quarter (20.2%) had a high risk of COVID-19 following risk quantification. The risk cuts across geographical locations and socio-economic status. Education was significantly associated with COVID-19 risk. The spatial interpolation map revealed that the farther a community was from the high-burden area, the lower the risk of COVID-19. Conclusion: There was a high prevalence of self-reported COVID-19 risk. Identified communities with COVID-19 high-risk burden in the risk mapping and those with stratified proximity to these areas need to be targeted by the government for a public health awareness campaign.

Cost of illness of non-communicable diseases in private and public health facilities in Nigeria: a qualitative and quantitative approach.

Introduction: the cost of illness (COI) of non-communicable diseases (NCDs) has detrimental effects on healthcare outcomes in addition to the serious economic impact on patients and their families. This study estimated and compared the COI of NCDs and its predictors in private and public health facilities (HF) in Ado-Ekiti, Nigeria. Methods: the study was carried out in selected HF (39 private; 11 public) using a comparative cross-sectional design with a mixed method of data collection. Quantitative data were collected from 348 hypertensive and/or diabetic patients (173 private; 175 public) using a semi-structured, interviewer-administered questionnaire while qualitative data were from 5 key informant interviews (KII) conducted with HF heads or their representatives. Results: the average monthly COI of NCDs was higher among patients in private (₦15,750.38±14,286.47 [US$43.75±39.68]) than in public HF (₦13,283.37±16,432.68 [US$ 36.90±45.65]) (P<0.001), however, the indirect cost was higher in public HF (private, ₦1,561.07 [US$4.34]; public, ₦3,739.26 [US$10.39]) (p<0.001). Predictors of COI of NCDs identified were income and admission in both groups. Additionally, age, payment method, type of NCDs, having two or more complications, and exercise were identified in private while socioeconomic status, length of diagnosis, and alcohol were identified in public HF. The KII revealed a long waiting time for the public HF patients which accounted for the huge indirect cost. Conclusion: the study found a huge indirect cost in the public HF that could be minimized by developing policies that would reduce the waiting time of patients. Government and private interventions targeting identified predictors should be applied to reduce the financial burden of NCD.

Comparative assessment of health-related quality of life among hypertensive patients attending state and federal government teaching hospitals in Ekiti State, Nigeria.

Background: Hypertension is a serious health problem and it is one of the diseases that impair health-related quality of life. The central tenet of care should be to improve health-related quality of life and overall well-being and not just be limited to improving clinical outcomes. This study assesses and compares health-related quality of life and its predictors among hypertensive patients in two government hospitals in Ekiti State, Nigeria. Methods: This was a comparative cross-sectional study involving 440 hypertensive patients (220 in each group), recruited using a systematic sampling technique within the hospitals. Data on socio-demographic, economic and clinical characteristics including the cost of care for hypertension were collected from the patients. The WHOQoL-BREF questionnaire was used to assess health-related quality of life. Data were entered and analyzed using IBM SPSS Statistics for Windows, Version 22.0. Results: All domains of health-related quality of life were better among patients in federal government teaching hospitals, however, only the physical (T = -7.932, p < 0.001) and overall (T = -2.783, p = 0.006) domains were of statistical significance. An inverse relationship between cost and health-related quality of life was found in the two hospitals (State: r = -0.224, p = 0.001; Federal: r = -0.378, p < 0.001). Identified predictors of health-related quality of life were age, locality of residence, income, number of complications, exercise and smoking in both hospitals. Other predictors were marital status, living arrangement, occupation, number of medications, and involvement in religious and spiritual activities among patients in the state government teaching hospital; household size, length of diagnosis, and indirect cost among patients in the federal government teaching hospital. Conclusion: There is a need to support hypertensive patients in the state government teaching hospitals to reduce the inequality of low health-related quality of life among them. Identified predictors should be taken into consideration when putting in place policies that will improve the health-related quality of life of these patients.