The effect of lockdown regulations on SARS-CoV-2 infectivity in Gauteng Province, South Africa

Background. On 26 March 2020, the South African (SA) government initiated a 21-day national level 5 lockdown which was subsequently eased off and downgraded to level 4 on 1 May and to level 3 on 1 June. The effect of lockdown measures on SARS-CoV-2 infectivity is currently uncertain. In this article, we analyse the effects of the lockdown measures on the SARS-CoV-2 epidemic in one of the epicentres in SA.Objectives. To measure the effects of lockdown measures introduced in SA on SARS-CoV-2 attack rates (ARs, the percentage of individuals who tested positive in a specified time period) in Gauteng Province during a 4-month period (March - June 2020).Methods. In this retrospective cohort study, we used a comprehensive database from an independent pathology laboratory in Gauteng. We analysed trends of positivity rates of reverse transcription polymerase chain reaction tests done during the 4-month period. The ARs are reported over time (unweighted and age-weighted 14-day moving averages) by age groups, gender, and different regions/districts in Gauteng.Results. A total of 162 528 tests were performed at a private laboratory between 5 March and 30 June 2020, of which 20 574 were positive (overall AR 12.7%). These positive tests constituted 44.8% of all positive cases in the province (20 574/45 944). Sixty-two percent of all tests were done in June during lockdown level 3. There was an exponential increase in the AR in June (18.3%) when lockdown was eased to level 3, in comparison with 4.2% (March), 2.2% (April) and 3.3% (May). The increase in June was seen in all the age groups, although it was more pronounced in the 21 - 60 years age groups than the younger (0 - 20 years) and older (>60 years) age groups. The AR was significantly higher in males (13.2%) compared with females (12.1%) (χ2 test, p<0.0001).Conclusions. The findings of this study testify to the rapid increase in ARs resulting from easing of the lockdown regulations, especially to level 3 in June. Of concern is the upward trend in the AR across all age groups, especially <20 years (15.9%), which was not reported in other parts of the world. Population age dynamics should therefore be considered when taking future decisions about lockdown regulations

HIV and COVID-19 co-infection : mild infection or prolonged transmission

BACKGROUND. Comorbid conditions may be associated with severe COVID-19. However, there is no evidence to suggest that people living with HIV have a higher risk of contracting SARS-CoV-2 or, if infected, have more severe disease. OBJECTIVE. To describe three patients with HIV and COVID-19 co-infection. METHOD. The study was conducted in a private hospital in Gauteng Province, South Africa. All three patients were known to have HIV disease and were treated with chronic antiretroviral medication. All patients admitted to the unit were screened for chronic conditions such as HIV, tuberculosis, diabetes and hypertension. They were admitted to the hospital after being diagnosed with COVID-19, this being confirmed by positive reverse transcription polymerase chain reaction (RT-PCR) tests. RESULTS. The combination of HIV and SARS-CoV-2 (HIVCO) with comorbidities in case 1 (dialysis-dependent end-stage renal failure and hypertension) resulted in severe illness, a long hospital stay and protracted viral shedding. The protracted shedding pattern (>60 days) was confirmed by multiple positive RT-PCR tests and positive viral cultures obtained after 60 days. Despite comorbidities, case 2 (Takayasu’s disease in remission, dyslipidaemia and previous deep vein thrombosis) and case 3 (hypertension and diabetes) presented with mild illness. The mild clinical course and negative RT-PCR tests in cases 2 and 3 indicated resolution of infection. CONCLUSION. Patients with HIVCO and comorbidities may present with mild or severe illness. Unusually long SARS-CoV-2 shedding is a risk for disease transmission, and its association with HIV, other immunocompromised conditions and comorbidities is unclear. We describe a shedding classification that may assist in identifying and managing infectious subsets of patients. Multiple SARS-CoV-2 tests and viral cultures may be necessary to confirm protracted shedding.http://www.samj.org.za/index.php/samjam2021School of Health Systems and Public Health (SHSPH

The effect of lockdown regulations on SARS-CoV-2 infectivity in Gauteng Province, South Africa

BACKGROUND. On 26 March 2020, the South African (SA) government initiated a 21-day national level 5 lockdown which was subsequently eased off and downgraded to level 4 on 1 May and to level 3 on 1 June. The effect of lockdown measures on SARS-CoV-2 infectivity is currently uncertain. In this article, we analyse the effects of the lockdown measures on the SARS-CoV-2 epidemic in one of the epicentres in SA. OBJECTIVES. To measure the effects of lockdown measures introduced in SA on SARS-CoV-2 attack rates (ARs, the percentage of individuals who tested positive in a specified time period) in Gauteng Province during a 4-month period (March - June 2020). METHODS. In this retrospective cohort study, we used a comprehensive database from an independent pathology laboratory in Gauteng. We analysed trends of positivity rates of reverse transcription polymerase chain reaction tests done during the 4-month period. The ARs are reported over time (unweighted and age-weighted 14-day moving averages) by age groups, gender, and different regions/districts in Gauteng. RESULTS. A total of 162 528 tests were performed at a private laboratory between 5 March and 30 June 2020, of which 20 574 were positive (overall AR 12.7%). These positive tests constituted 44.8% of all positive cases in the province (20 574/45 944). Sixty-two percent of all tests were done in June during lockdown level 3. There was an exponential increase in the AR in June (18.3%) when lockdown was eased to level 3, in comparison with 4.2% (March), 2.2% (April) and 3.3% (May). The increase in June was seen in all the age groups, although it was more pronounced in the 21 - 60 years age groups than the younger (0 - 20 years) and older (>60 years) age groups. The AR was significantly higher in males (13.2%) compared with females (12.1%) (χ2 test, p<0.0001). CONCLUSIONS. The findings of this study testify to the rapid increase in ARs resulting from easing of the lockdown regulations, especially to level 3 in June. Of concern is the upward trend in the AR across all age groups, especially <20 years (15.9%), which was not reported in other parts of the world. Population age dynamics should therefore be considered when taking future decisions about lockdown regulations.http://www.samj.org.zaam2021School of Health Systems and Public Health (SHSPH

Trends in cases, hospitalizations, and mortality related to the Omicron BA.4/BA.5 subvariants in South Africa

BACKGROUND : In this study, we compared admission incidence risk and the risk of mortality in the Omicron BA.4/BA.5 wave to previous waves. METHODS : Data from South Africa’s SARS-CoV-2 case linelist, national COVID-19 hospital surveillance system, and Electronic Vaccine Data System were linked and analyzed. Wave periods were defined when the country passed a weekly incidence of 30 cases/ 100 000 population. In-hospital case fatality ratios (CFRs) during the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves were compared using post-imputation random effect multivariable logistic regression models. RESULTS : The CFR was 25.9% (N=37 538 of 144 778), 10.9% (N=6123 of 56 384), and 8.2% (N=1212 of 14 879) in the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves, respectively. After adjusting for age, sex, race, comorbidities, health sector, and province, compared with the Omicron BA.4/BA.5 wave, patients had higher risk of mortality in the Omicron BA.1/BA.2 wave (adjusted odds ratio [aOR], 1.3; 95% confidence interval [CI]: 1.2–1.4) and Delta wave (aOR, 3.0; 95% CI: 2.8–3.2). Being partially vaccinated (aOR, 0.9; 95% CI: .9–.9), fully vaccinated (aOR, 0.6; 95% CI: .6–.7), and boosted (aOR, 0.4; 95% CI: .4–.5) and having prior laboratory-confirmed infection (aOR, 0.4; 95% CI: .3–.4) were associated with reduced risks of mortality. CONCLUSIONS : Overall, admission incidence risk and in-hospital mortality, which had increased progressively in South Africa’s first 3 waves, decreased in the fourth Omicron BA.1/BA.2 wave and declined even further in the fifth Omicron BA.4/BA.5 wave. Mortality risk was lower in those with natural infection and vaccination, declining further as the number of vaccine doses increased.https://academic.oup.com/cid/am2024Human NutritionSDG-03:Good heatlh and well-bein

Factors that could explain the increasing prevalence of type 2 diabetes among adults in a Canadian province: a critical review and analysis

Abstract: Background: The prevalence of diabetes has increased since the last decade in New Brunswick. Identifying factors contributing to the increase in diabetes prevalence will help inform an action plan to manage the condition. The objective was to describe factors that could explain the increasing prevalence of type 2 diabetes in New Brunswick since 2001. Methods: A critical literature review was conducted to identify factors potentially responsible for an increase in prevalence of diabetes. Data from various sources were obtained to draw a repeated cross-sectional (2001–2014) description of these factors concurrently with changes in the prevalence of type 2 diabetes in New Brunswick. Linear regressions, Poisson regressions and Cochran Armitage analysis were used to describe relationships between these factors and time. Results: Factors identified in the review were summarized in five categories: individual-level risk factors, environmental risk factors, evolution of the disease, detection effect and global changes. The prevalence of type 2 diabetes has increased by 120% between 2001 and 2014. The prevalence of obesity, hypertension, prediabetes, alcohol consumption, immigration and urbanization increased during the study period and the consumption of fruits and vegetables decreased which could represent potential factors of the increasing prevalence of type 2 diabetes. Physical activity, smoking, socioeconomic status and education did not present trends that could explain the increasing prevalence of type 2 diabetes. During the study period, the mortality rate and the conversion rate from prediabetes to diabetes decreased and the incidence rate increased. Suggestion of a detection effect was also present as the number of people tested increased while the HbA1c and the age at detection decreased. Period and birth cohort effect were also noted through a rise in the prevalence of type 2 diabetes across all age groups, but greater increases were observed among the younger cohorts. Conclusions: This study presents a comprehensive overview of factors potentially responsible for population level changes in prevalence of type 2 diabetes. Recent increases in type 2 diabetes in New Brunswick may be attributable to a combination of some individual-level and environmental risk factors, the detection effect, the evolution of the disease and global changes