Stronger impact of COVID-19 in nursing homes of a French Region during the second pandemic wave

Objectives Quantify the effects of characteristics of nursing homes and their surrounding on the spread of COVID-19 outbreaks and assess the changes in resident protection between the first two waves (March 1 to July 31 and August 1 to December 31, 2020). Design An observational study was carried out on data on COVID-19 outbreaks extracted from a database that monitored the spread of the virus in nursing homes. Setting and participants The study concerned all 937 nursing homes with > 10 beds in Auvergne-Rhône-Alpes Region, France. Methods The rate of nursing homes with at least one outbreak and the cumulative number of deaths were modeled for each wave. Results During the second (vs. the first wave), the proportion of nursing homes that reported at least one outbreak was higher (70% vs. 56%) and the cumulative number of deaths more than twofold (3348 vs. 1590). The outbreak rate was significantly lower in public hospital-associated nursing homes than in private for-profit ones. During the second wave, it was lower in public and private not-for-profit nursing homes than in private for-profit ones. During the first wave, the probability of outbreak and the mean number of deaths increased with the number of beds (p < 0.001). During the second wave, the probability of outbreak remained stable in > 80-bed institutions and, under proportionality assumption, the mean number of death was less than expected in > 100-bed institutions. The outbreak rate and the cumulative number of deaths increased significantly with the increase in the incidence of hospitalization for COVID-19 in the surrounding populations. Conclusions and implications The outbreak in the nursing homes was stronger during the second than the first wave despite better preparedness and higher availabilities of tests and protective equipment. Insufficient staffing, inadequate rooming, and suboptimal functioning should find solutions before future epidemics.

Self-medication against COVID-19 in health workers in Conakry, Guinea.

Data regarding the prevalence and consequences of self-medication during the COVID-19 pandemic in Africa are very limited. The study aimed to explore the frequency and risk factors of self-medication against COVID-19 by health personnel in this study. This cross-sectional study took place in June 2021, in Conakry, in the all three national hospitals and the six community medical centers, and five primary health centers. A multivariate logistic regression model was performed to identify factors associated with self-medication. A total of 975 health workers with a median age of 31 (IQR: 27-40) years, with 504 (51.7%) women were included. The majority were clinicians: physicians (33.1%) or nurses (33.1%). Of all, 46.2% reported having had at least one COVID-19 symptom during the 12 months preceding the survey. The proportion of self-medication was 15.3% among national hospital staff, 12.20% in municipality medical centers and 22.6% in primary health centers (p=0.06). More than two-thirds (68.7%) who selfmedicated did not have a test for SARSCoV- 2 infection. They took antibiotics including azithromycin, amoxicillin, ampicillin (42.2%), acetaminophen (37.4%), vitamin C (27.9%), hydroxychloroquine (23.8%) and medicinal plants (13.6%). The median duration of self-medication was 4 days. Fatigue or asthenia, sore throat, loss of smell and sore throat of a close person were independently associated with selfmedication. Health care workers largely practiced self-medication during the Covid pandemic and without diagnostic testing. The results suggest the need for training and sensitization of medical personnel to avoid the consequences of the molecules used, including hepatotoxicity and antibiotic resistance.

High and Rapid Increase in Seroprevalence for SARS-CoV-2 in Conakry, Guinea: Results From 3 Successive Cross-Sectional Surveys (ANRS COV16-ARIACOV).

We conducted 3 successive seroprevalence surveys, 3 months apart, using multistage cluster sampling to measure the extent and dynamics of the severe acute respiratory syndrome coronavirus 2 epidemic in Conakry, the capital city of Guinea. Seroprevalence increased from 17.3% (95% CI, 12.4%-23.8%) in December 2020 during the first survey (S1) to 28.9% (95% CI, 25.6%-32.4%) in March/April 2021 (S2), then to 42.4% (95% CI, 39.5%-45.3%) in June 2021 (S3). This significant overall trend of increasing seroprevalence (P < .0001) was also significant in every age class, illustrating a sustained transmission within the whole community. These data may contribute to defining cost-effective response strategies.

High Prevalence of Anti-Severe Acute Respiratory Syndrome Coronavirus 2 (Anti-SARS-CoV-2) Antibodies After the First Wave of Coronavirus Disease 2019 (COVID-19) in Kinshasa, Democratic Republic of the Congo: Results of a Cross-sectional Household-Based Survey.

BACKGROUND: In October 2020, after the first wave of coronavirus disease 2019 (COVID-19), only 8290 confirmed cases were reported in Kinshasa, Democratic Republic of the Congo, but the real prevalence remains unknown. To guide public health policies, we aimed to describe the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibodies in the general population in Kinshasa. METHODS: We conducted a cross-sectional, household-based serosurvey between 22 October 2020 and 8 November 2020. Participants were interviewed at home and tested for antibodies against SARS-CoV-2 spike and nucleocapsid proteins in a Luminex-based assay. A positive serology was defined as a sample that reacted with both SARS-CoV-2 proteins (100% sensitivity, 99.7% specificity). The overall weighted, age-standardized prevalence was estimated and the infection-to-case ratio was calculated to determine the proportion of undiagnosed SARS-CoV-2 infections. RESULTS: A total of 1233 participants from 292 households were included (mean age, 32.4 years; 764 [61.2%] women). The overall weighted, age-standardized SARS-CoV-2 seroprevalence was 16.6% (95% CI: 14.0-19.5%). The estimated infection-to-case ratio was 292:1. Prevalence was higher among participants ≥40 years than among those <18 years (21.2% vs 14.9%, respectively; P < .05). It was also higher in participants who reported hospitalization than among those who did not (29.8% vs 16.0%, respectively; P < .05). However, differences were not significant in the multivariate model (P = .1). CONCLUSIONS: The prevalence of SARS-CoV-2 is much higher than the number of COVID-19 cases reported. These results justify the organization of a sequential series of serosurveys by public health authorities to adapt response measures to the dynamics of the pandemic.

COVID-19 outbreaks in nursing homes: A strong link with the coronavirus spread in the surrounding population, France, March to July 2020.

BACKGROUND: Worldwide, COVID-19 outbreaks in nursing homes have often been sudden and massive. The study investigated the role SARS-CoV-2 virus spread in nearby population plays in introducing the disease in nursing homes. MATERIAL AND METHODS: This was carried out through modelling the occurrences of first cases in each of 943 nursing homes of Auvergne-Rhône-Alpes French Region over the first epidemic wave (March-July, 2020). The cumulative probabilities of COVID-19 outbreak in the nursing homes and those of hospitalization for the disease in the population were modelled in each of the twelve Départements of the Region over period March-July 2020. This allowed estimating the duration of the active outbreak period, the dates and heights of the peaks of outbreak probabilities in nursing homes, and the dates and heights of the peaks of hospitalization probabilities in the population. Spearman coefficient estimated the correlation between the two peak series. RESULTS: The cumulative proportion of nursing homes with COVID-19 outbreaks was 52% (490/943; range: 22-70% acc. Département). The active outbreak period in the nursing homes lasted 11 to 21 days (acc. Département) and ended before lockdown end. Spearman correlation between outbreak probability peaks in nursing homes and hospitalization probability peaks in the population (surrogate of the incidence peaks) was estimated at 0.71 (95% CI: [0.66; 0.78]). CONCLUSION: The modelling highlighted a strong correlation between the outbreak in nursing homes and the external pressure of the disease. It indicated that avoiding disease outbreaks in nursing homes requires a tight control of virus spread in the surrounding populations.

The COVID-19 pandemic is deepening the health crisis in South Kivu, Democratic Republic of Congo.

OBJECTIVE: The outbreak of coronavirus disease 2019 (COVID-19) in South Kivu, Democratic Republic of Congo raised concerns regarding additional morbidity and mortality. Updating these indicators before a second wave is essential in order to prepare for additional help. METHODS: From mid-May to mid-December 2020, weekly surveys were undertaken in sampled streets from 10 health areas to quantify the use of barrier measures, and interview pedestrians about sickness and deaths in their households. Crude death rates (CDRs) were estimated. RESULTS: Minimal use or no use of face masks was observed in at least half of the streets. From May to December 2020, the number of suspected cases of COVID-19 increased six-fold (P < 0.05). Of deaths within 30 days preceding the interviews, 20% were considered to be related to COVID-19. The monthly CDRs at the beginning and end of the study were approximately 5 and 25 per 1000 population, respectively (P < 0.05); that is, annual CDRs of 60 and 260 per 1000 population, respectively. Thus, during the first wave, the estimated mortality rate increased by 50% compared with previous years, and increased at least four-fold by the end of 2020. CONCLUSION: Despite possible overestimations, the excess mortality in South Kivu is extremely concerning. This crisis calls for a rapid response and increased humanitarian assistance.

A dashboard for monitoring preventive measures in response to COVID-19 outbreak in the Democratic Republic of Congo.

BACKGROUND: In most health areas, an information system is necessary for an effective fight against COVID-19. Current methods for surveillance of diseases with epidemic potential do not include monitoring the adherence to preventive measures. Furthermore, modern data collection methods depend often on technologies (e.g., cameras or drones) that are hardly available in low-income countries. Simpler solutions could be just as effective. METHODS: A dashboard was used over a whole week to monitor preventive measures in Bukavu (DRC) by mid-May 2020. It was designed to collect from street passers-by information on the adherence to barrier measures, the level of awareness of these measures, the opinion on their usefulness, and the health status of people in the households. RESULTS: Creating a dashboard and collecting the necessary data proved feasible. The use of barrier measures was very limited and that of masks practically nil despite repeated recommendations from the health authorities. The end of each day was the worst moment due to clearly insufficient distancing. Barrier measures were significantly more used in areas where they were best known and most acknowledged. At the time of the study, there were few sick people and only rare severe cases were attributed to COVID-19. CONCLUSIONS: Creating COVID-19 situation dashboards in limited-resource metropoles is feasible. They give real-time access to data that help fight the epidemic. The findings of this pilot study call for a rapid community awareness actions to back national media-based prevention campaigns.

Potential lethal outbreak of coronavirus disease (COVID-19) among the elderly in retirement homes and long-term facilities, France, March 2020.

Motivated by the potential devastating effect of a COVID-19 outbreak in retirement homes and long-term facilities for dependent elderly, we present the impact of worst-case scenarios in French institutions using a specific age structure and case-age fatality ratios. The death toll could equal the yearly death toll caused by seasonal influenza in those older than 65 years or could largely exceed that, depending on the final attack rate and proportion of infected institutions.