Influence of population density and access to sanitation on Covid-19 in Mozambique

In 2020, as COVID-19 spread worldwide, prestigious entities published faulty predictions about the level of dissemination, especially when describing African countries and others with "weak healthcare systems." How could the best fall so short, even when using well-known epidemiological variables to predict the behavior of a hygiene-related malady? It might have been due to insufficient data since COVID-19 was a novelty, still poorly understood. The current study aimed to analyze how two variables ­population density and percentage of people with access to improved sanitation ­affected the number of confirmed COVID-19 cases in Mozambique by February 2021, almost one year since the first case in the country. All data were publicly available: population density in Census 2017, access to sanitation in the Mozambique Public Expenditure Review 2014, and the number of COVID-19 cases in the Ministry of Health's COVID-19 daily bulletin (no. 332). JASP 0.13.1.0 allowed correlating all variables, and MicrosoftExcel™ was chosen to perform fitting analysis to model the algebraic relationship between the number of cases and the other variables. The cases showed a positive correlation (r = 0.663) with density, and their relationship was consistent with a cubic function. Sanitation coverage also showed a positive correlation (r = 0.679), but the most straightforward algebraic representation was a quadratic function. The impact of population density on the number of COVID-19 cases was intuitive, but the logic points towards the highest number of cases where sanitation facilities lacked the most. Thus, the influence of other factors outweighed the effect of sanitation, or people tend to be careless before the sense of security where the sanitation is better. Nevertheless, these findings can support predictions and decision-making, and the population needs to abide by the Government's recommendations.

Potential impact of temperature and atmospheric pressure on the number of cases of COVID-19 in Mozambique, Southern Africa

The potential reasons why COVID-19 is not spreading rapidly in Sub-Saharan Africa include sociopolitical, biological and environmental variables. Among the latter, some studies indicate temperature and atmospheric pressure as significantly influential. Could they have impact on the number of COVID-19 cases in Mozambique? The aim of this study is to analyze the relationships between weather and the frequency of confirmed COVID-19 cases in Mozambique, Southern Africa. The study was conducted in Mozambique, Maputo area (Province and City) and Nampula Province. Daily history of weather variables ­ daily maximum and minimum temperatures and atmospheric pressure ­ was obtained from three online databases (AccuWeather, Time and Date AS and WeatherSpark) and the number of COVID-19 cases from official Government's daily Bulletins. The main statistical analyses were Pearson correlations between the variables. The first case was observed in the Maputo area on 22 March, 2020 and the cases in Mozambique increased exponentially up to 769 by 24 June, 2020. The first three cases in Nampula province were observed on 24 May 2020 but its frequency surpassed Maputo area's within one month. Temperatures showed negative correlations with the number of cases in all areas and pressure showed positive correlations in Maputo area and Nampula Province. A bubble chart allowed the visualization of the combined relationship of both weather variables and the number of cases, suggesting that the number of cases increases as temperature decreases and pressure increases. Temperature and atmospheric pressure seems to be correlated with the number of confirmed cases of COVID-19 in Mozambique. Thus, decision-makers should consider weather as a predictor of the rate at which the pandemic is spreading in the country

Stress tolerance of Staphylococcus aureus with different antibiotic resistance profiles.

Staphylococcus aureus (S. aureus) is a zoonotic bacterium and is among the most important pathogens causing bacterial foodborne diseases. In recent years, disease caused by antibiotic-resistant S. aureus is a serious clinical problem that poses a great threat to public health. In this study, we examined the drug-resistance phenotypes and genotypes of 9 S. aureus strains. One strain was obtained from the China Center for Type Culture Collection (CCTCC), and the remaining eight strains were isolated from food. Two common methods (the Kirby-Bauer disk diffusion and broth microdilution methods) were used to detect bacterial drug resistance. Then, we analysed the relationship between the bacterial drug resistance phenotypes and genotypes. We found that some S. aureus strains isolated from food were drug-resistant or even multi-drug resistant and that there was not a perfect match between resistance phenotypes and genotypes. The viabilities of the drug-sensitive (DS), drug-resistant (DR), and multi-drug resistant (MDR) S. aureus strains were also compared when they were exposed to conditions of acid (HCl, pH = 1.5), heat (63 °C), and osmotic pressure (30% NaCl). The results showed that the DR and MDR bacterial strains had survival rates similar to or higher than those of the DS strains under environmental stress.