Assessment of indoor radon distribution and seasonal variation within the Kpando Municipality of Volta Region, Ghana.

This study uses CR-39 radon detectors to examine radon distributions, seasonal indoor radon variations, correction factors, and the influence of building materials and characteristics on indoor radon concentration in 120 dwellings. The study also determines the spatial distribution of radon levels using the ArcGIS geostatistical method. Radon detectors were exposed in bedrooms from April to July (RS), August to November (DS); December to March (HS), and January-December (YS) from 2021 to 2022. The result for the radon levels during the weather seasons were; 32.3 to 190.1 Bqm-3 (80.9 ± 3.2 Bq/m3) for (RS), 30.8 to 151.4 Bqm-3 (68.5 ± 2.7 Bqm-3) for HS and 24.8 to 112.9 Bqm-3(61.7 ± 2.1 Bqm-3) for DS, and 25.2 to 145.2 Bq/m3 (69.4 ± 2.7 Bqm-3). The arithmetic mean for April to July season was greater than August to November. The correction factors associated with this study ranged from 0.9 to 1.2. The annual effective dose (AE) associated with radon data was varied from 0.6 to 4.04 mSv/y (1.8 ± 0.1 mSv/y). The April to July period which was characterized by rains recorded the highest correlation coefficient and indoor radon concentration. Distribution and radon mapping revealed radon that the exposure to the occupant is non-uniformly spread across the studied dwellings. 15.4% of the studied data exceeded WHO reference values of 100 Bq/m3. The seasonal variation, dwelling age, and building materials were observed to have a substantial impact on the levels of radon concentration within the buildings.

Assessment of natural radioactivity, radon gas and soil characteristics along the Volta Lake in the Kpando municipality of Volta region, Ghana.

Assessment of radionuclides, indoor radon (222RnI), radon exhalation (222Rnex), and soil characteristics in the coastal part of Kpando has been studied using HPGe, CR-39 and sieving techniques. Statistical analysis between radionuclides, radon levels and soil characteristics was done using Pearson's correlation. The mean radionuclide concentration, radon levels and soil characteristics were obtained as 226Ra (23.1 ± 1.4 Bq per kg), 232Th (34.6 ± 2.9 Bq per kg), 40K (187.1 ± 13.7 Bq per kg), 222RnI (64.70 ± 2.7 Bq per m3), 222Rnex (7.9 ± 0.5 µBq per m2h), sandy (45.9 ± 3.9%), silt (40.7 ± 3.1%), clay (13.5 ± 0.8%), porosity (0.6 ± 0.1) and moisture (7.6 ± 0.8%). Radiological effects estimated were within recommended limits. The maximum positive and negative coefficients exist between 222Ra/222Rnex (1.0) and 222Rnex/MC (-0.9), respectively. Radon exhalation correlates better with soil characteristics. The statistical analysis indicated that soil characteristics have significant effects on radionuclides and radon levels in soils and dwellings.

Risk factors for COVID-19 virus infection among health workers: A case-control study in the Bono East Region of Ghana.

BACKGROUND: Disproportionately high rates of COVID-19 infection among health workers prompts the need to identify the risk factors to help guide the design and implementation of interventions. The aim of this study was to characterize the risk factors for COVID-19 infection among health workers. METHODS: A case-control study was designed to recruit 154 health workers who tested positive for the COVID-19 virus and 308 who tested negative from 8 hospitals and 11 health directorates in the Bono East Region of Ghana. Crude and adjusted logistic regression analysis was used to determine risk factors. RESULTS: Hand hygiene compliance for the recommended moments ranged from 55.3% to 77.4%. Personal protective equipments (PPE) use was 59.5% when patients' COVID-19 status was unknown and at least 90.7% when patient was positive. We identified years of practice experience (adjusted odds ratio (AOR) = 1.81; 95% CI: 1.07, 3.07; P = .028), adherence to infection prevention and control (IPC) when in contact with patients whose COVID-19 status is unspecified (AOR = 1.71; 95% CI: 1.09, 2.70; P = .020) and type of facility (AOR = 1.69, 95% CI: 1.09, 2.62; P = .019) as risk factors. CONCLUSION: The findings underscore the need for health workers to improve in COVID-19 risk perception.