Incidence rate and predictors of COVID-19 in the two largest cities of Burkina Faso - prospective cohort study in 2021 (ANRS-COV13).

BACKGROUND: Early data on COVID-19 (based primarily on PCR testing) indicated a low burden in Sub-Saharan Africa. To better understand this, this study aimed to estimate the incidence rate and identify predictors of SARS-CoV-2 seroconversion in the two largest cities of Burkina Faso. This study is part of the EmulCOVID-19 project (ANRS-COV13). METHODS: Our study utilized the WHO Unity protocol for cohort sero-epidemiological studies of COVID-19 in general population. We conducted random sampling stratified by age group and sex. Individuals aged 10 years and older in the cities of Ouagadougou and Bobo-Dioulasso, Burkina Faso were included and surveyed at 4 time points, each 21 days apart, from March 3 to May 15, 2021. WANTAI SARS-CoV-2 Ab ELISA serological tests were used to detect total antibodies (IgM, IgG) in serum. Predictors were investigated using Cox proportional hazards regression. RESULTS: We analyzed the data from 1399 participants (1051 in Ouagadougou, 348 in Bobo-Dioulasso) who were SARS-CoV-2 seronegative at baseline and had at least one follow-up visit. The incidence rate of SARS-CoV-2 seroconversion was 14.3 cases [95%CI 13.3-15.4] per 100 person-weeks. The incidence rate was almost three times higher in Ouagadougou than in Bobo-Dioulasso (Incidence rate ratio: IRR = 2.7 [2.2-3.2], p < 0.001). The highest incidence rate was reported among women aged 19-59 years in Ouagadougou (22.8 cases [19.6-26.4] per 100 person-weeks) and the lowest among participants aged 60 years and over in Bobo-Dioulasso, 6.3 cases [4.6-8.6] per 100 person-weeks. Multivariable analysis showed that participants aged 19 years and older were almost twice as likely to seroconvert during the study period compared with those aged 10 to 18 years (Hazard ratio: HR = 1.7 [1.3-2.3], p < 0.001). Those aged 10-18 years exhibited more asymptomatic forms than those aged 19 years and older, among those who achieved seroconversion (72.9% vs. 40.4%, p < 0.001). CONCLUSION: The spread of COVID-19 is more rapid in adults and in large cities. Strategies to control this pandemic in Burkina Faso, must take this into account. Adults living in large cities should be the priority targets for vaccination efforts against COVID-19.

[Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy: The EpiCovAir study]. / Esposizione a lungo termine a inquinamento dell'aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir.

BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated. OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy. DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated. SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used. MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure. RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 µg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses. CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found.

Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2.

The sanitary emergency caused by COVID-19 has compromised countries and generated a worldwide health and economic crisis. To provide support to the countries' responses, numerous lines of research have been developed. The spotlight was put on effectively and rapidly diagnosing and predicting the evolution of the pandemic, one of the most challenging problems of the past months. This work contributes to the existing literature by developing a two-step methodology to analyze the transmission rate, designing models applied to territories with similar pandemic behavior characteristics. Virus transmission is considered as bacterial growth curves to understand the spread of the virus and to make predictions about its future evolution. Hence, an analytical clustering procedure is first applied to create groups of locations where the virus transmission rate behaved similarly in the different outbreaks. A curve decomposition process based on an iterative polynomial process is then applied, obtaining meaningful forecasting features. Information of the territories belonging to the same cluster is merged to build models capable of simultaneously predicting the 14-day incidence in several locations using Evolutionary Artificial Neural Networks. The methodology is applied to Andalusia (Spain), although it is applicable to any region across the world. Individual models trained for a specific territory are carried out for comparison purposes. The results demonstrate that this methodology achieves statistically similar, or even better, performance for most of the locations. In addition to being extremely competitive, the main advantage of the proposal lies in its complexity cost reduction. The total number of parameters to be estimated is reduced up to 93.51% for the short term and 93.31% for the mid-term forecasting, respectively. Moreover, the number of required models is reduced by 73.53% and 58.82% for the short- and mid-term forecasting horizons.

The effect of neighborhood characteristics on HIV risk behaviors, HIV testing, and Covid-19 incidence in Louisiana

Both the HIV pandemic and the COVID-19 pandemic have highlighted underlying racial and socioeconomic health disparities in Louisiana, as well as in the United States. Neighborhood factors, such as community violence and social vulnerability, likely play a significant role in these disparities.The goals of this study were to examine the relationship between community violence exposure and HIV sexual risk behaviors and to examine the impact of neighborhood-level social vulnerability on HIV testing practices and COVID-19 incidence.Data from the National HIV Behavioral Surveillance System, the CDC Social Vulnerability Index (SVI) Database, and the Louisiana Department of Health were analyzed. The CDC SVI was used to measure neighborhood-level social vulnerability, which comprises four related factors: socioeconomic status, household composition and disability, minority and language, and housing characteristics and transportation.First, the relationship between community violence exposure and HIV sexual risk behaviors was examined among an age-diverse population of heterosexually active adults. A positive association was observed between community violence exposure and HIV sexual risk behaviors. Gender did not modify this relationship.Second, the relationship between neighborhood-level social vulnerability and recent HIV testing history was examined. Neighborhood-level socioeconomic status was the only social vulnerability factor observed to be associated with recent HIV testing, where individuals residing in lower socioeconomic neighborhoods had lower odds of receiving a recent HIV test than those residing in higher socioeconomic neighborhoods. This association diminished as age increased.Third, the relationship between social vulnerability and COVID-19 incidence during the first six months of the COVID-19 pandemic within Louisiana census tracts was examined. All four factors measuring social vulnerability were found to be associated with COVID-19 incidence;Louisiana census tracts with higher levels of overall social vulnerability exhibited higher levels of COVID-19 incidences. The results of this study provide further evidence that neighborhood characteristics can influence health behaviors (e.g., sexual risk behaviors), access to healthcare (e.g., HIV testing), and health outcomes (e.g., COVID-19 infections). In conclusion, future public health initiatives should focus on identifying and removing barriers to health within identified vulnerable neighborhoods. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

The impact of the COVID-19 pandemic on regional inequalities in Romania. Spotlight on unemployment and health conditions

For a long time, inequalities have existed across the population and between different communities and groups. Although regional inequality is a topic of interest among scholars and policy makers, only recently have they been increasingly investigated at local territorial units. The economic shock related to the COVID-19 crisis, which resulted from the lockdown and significant decline in economic activity in many sectors, has affected all regions, but not in the same way or with a similar intensity. Assessing some regional indicators available in the first period of the ongoing COVID-19 crisis depicting the quality of life, it is becoming evident that new regional disparities emerge and interact with many of the pre-existing inequalities. This paper aims to provide new insights on the impact of the COVID-19 pandemic on inequalities across two dimensions, namely employment and health conditions, with relevance for the standard of living. By investigating past and current evolutions of some indicators, as reflected at the NUTS3 territorial level in Romania and the use of spatial analysis, our study shows that new fissures generated by the health crisis have deepened the existing inequalities at the regional level along various key dimensions such as gender, age, education, and rural–urban and local geography. This empirical study, considering traditional measurements of inequality and relevant spatial investigation, evaluates the intensity of inequalities across all Romanian counties. © 2023 The Authors. Regional Science Policy & Practice © 2023 Regional Science Association International.

Psychosocial Impact of the COVID-19 Pandemic on People With Type 1 Diabetes: Results of an Ecological Momentary Assessment Study.

Aims: Psychological distress due to living with diabetes, demanding self-management tasks, impacts on life, and risks of complications is common among people living with diabetes. COVID-19 could pose a new additional risk factor for psychological distress in this group. This study aimed to analyze levels of COVID-19-related burdens and fears, variables explaining these levels, and associations with the concurrent 7-day COVID-19 incidence in people with type 1 diabetes (T1D). Methods: A total of 113 people with T1D (58% women; age: 42.3 ± 9.9 years) participated in an ecological momentary assessment (EMA) study between December 2020 and March 2021. The participants reported daily levels of COVID-19-related burdens and fears over 10 consecutive days. Global ratings of COVID-19-related burdens and fears were assessed using questionnaires, as were current and previous levels of diabetes distress (PAID), acceptance (DAS), fear of complications (FCQ), depressive symptoms (CES-D), and diabetes self-management (DSMQ). Current levels of diabetes distress and depressive symptoms were compared with pre-pandemic ratings gained during an earlier study phase. Associations between burdens and fears, psychosocial and somatic aspects, and the concurrent 7-day incidence rate were analyzed using multilevel regression. Results: Diabetes distress and depressive symptoms reported during the pandemic were comparable to pre-pandemic levels (PAID: p = .89; CES-D: p = .38). Daily EMA ratings reflected relatively low mean COVID-19-related burdens and fears in everyday life. However, there was substantial day-to-day variation per person indicating higher burdens on specific days. Multilevel analyses showed that daily COVID-19-related burdens and fears were significantly predicted by pre-pandemic levels of diabetes distress and diabetes acceptance but were not associated with the concurrent 7-day incidence rate nor with demographic and medical variables. Conclusions: This study observed no increase in diabetes distress and depressive symptoms during the pandemic in people with T1D. The participants reported low to moderate levels of COVID-19-related burdens. COVID-19-related burdens and fears could be explained by pre-pandemic levels of diabetes distress and acceptance but not by demographic and clinical risk variables. The findings suggest that mental factors may constitute stronger predictors of COVID-19-related burdens and fears than objective somatic conditions and risks in middle-aged adults with T1D.

Correlation between UV Index, Temperature and Humidity with Respect to Incidence and Severity of COVID 19 in Spain.

BACKGROUND: Various studies support the inverse correlation between solar exposure and Coronavirus SARS-CoV-2 infection. In Spain, from the Canary Islands to the northern part of the country, the global incidence of COVID-19 is different depending on latitude, which could be related to different meteorological conditions such as temperature, humidity, and ultraviolet index (UVI). The objective of the present work was to analyze the association between UVI, other relevant environmental factors such as temperature and humidity, and the incidence, severity, and mortality of COVID-19 at different latitudes in Spain. METHODS: An observational prospective study was conducted, recording the numbers of new cases, hospitalizations, patients in critical units, mortality rates, and annual variations related to UVI, temperature, and humidity in five different provinces of Spain from January 2020 to February 2021. RESULTS: Statistically significant inverse correlations (Spearman coefficients) were observed between UVI, temperature, annual changes, and the incidence of COVID-19 cases at almost all latitudes. CONCLUSION: Higher ultraviolet radiation levels and mean temperatures could contribute to reducing COVID-19 incidence, hospitalizations, and mortality.

Impact of Selected Meteorological Factors on COVID-19 Incidence in Southern Finland during 2020-2021.

We modelled the impact of selected meteorological factors on the daily number of new cases of the coronavirus disease 2019 (COVID-19) at the Hospital District of Helsinki and Uusimaa in southern Finland from August 2020 until May 2021. We applied a DLNM (distributed lag non-linear model) with and without various environmental and non-environmental confounding factors. The relationship between the daily mean temperature or absolute humidity and COVID-19 morbidity shows a non-linear dependency, with increased incidence of COVID-19 at low temperatures between 0 to -10 °C or at low absolute humidity (AH) values below 6 g/m3. However, the outcomes need to be interpreted with caution, because the associations found may be valid only for the study period in 2020-2021. Longer study periods are needed to investigate whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a seasonal pattern similar such as influenza and other viral respiratory infections. The influence of other non-environmental factors such as various mitigation measures are important to consider in future studies. Knowledge about associations between meteorological factors and COVID-19 can be useful information for policy makers and the education and health sector to predict and prepare for epidemic waves in the coming winters.

The effect of neighborhood characteristics on HIV risk behaviors, HIV testing, and Covid-19 incidence in Louisiana

Both the HIV pandemic and the COVID-19 pandemic have highlighted underlying racial and socioeconomic health disparities in Louisiana, as well as in the United States. Neighborhood factors, such as community violence and social vulnerability, likely play a significant role in these disparities.The goals of this study were to examine the relationship between community violence exposure and HIV sexual risk behaviors and to examine the impact of neighborhood-level social vulnerability on HIV testing practices and COVID-19 incidence.Data from the National HIV Behavioral Surveillance System, the CDC Social Vulnerability Index (SVI) Database, and the Louisiana Department of Health were analyzed. The CDC SVI was used to measure neighborhood-level social vulnerability, which comprises four related factors: socioeconomic status, household composition and disability, minority and language, and housing characteristics and transportation.First, the relationship between community violence exposure and HIV sexual risk behaviors was examined among an age-diverse population of heterosexually active adults. A positive association was observed between community violence exposure and HIV sexual risk behaviors. Gender did not modify this relationship.Second, the relationship between neighborhood-level social vulnerability and recent HIV testing history was examined. Neighborhood-level socioeconomic status was the only social vulnerability factor observed to be associated with recent HIV testing, where individuals residing in lower socioeconomic neighborhoods had lower odds of receiving a recent HIV test than those residing in higher socioeconomic neighborhoods. This association diminished as age increased.Third, the relationship between social vulnerability and COVID-19 incidence during the first six months of the COVID-19 pandemic within Louisiana census tracts was examined. All four factors measuring social vulnerability were found to be associated with COVID-19 incidence;Louisiana census tracts with higher levels of overall social vulnerability exhibited higher levels of COVID-19 incidences. The results of this study provide further evidence that neighborhood characteristics can influence health behaviors (e.g., sexual risk behaviors), access to healthcare (e.g., HIV testing), and health outcomes (e.g., COVID-19 infections). In conclusion, future public health initiatives should focus on identifying and removing barriers to health within identified vulnerable neighborhoods. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Local socio-structural predictors of COVID-19 incidence in Germany.

Socio-economic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socio-economic driving factors of the COVID-19 epidemic is still incomplete. Based on linear random effects regression, an ecological model is derived to estimate COVID-19 incidence in German rural/urban districts from local socio-economic factors and popularity of political parties in terms of their share of vote. Thereby, records provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, are used to construct the dependent variable. Local socio-economic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Socio-economic parameters like per capita income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact on incidence. To the contrary, incidence significantly increases with population density and we observe a strong association with vote shares. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. In order to effectively combat the COVID-19 epidemic, public health policymakers are well-advised to account for social attitudes and behavioral patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive "markers" relevant for public health policy making.

Long-Term Care Home Size Association with COVID-19 Infection and Mortality in Catalonia in March and April 2020.

We aim to assess how COVID-19 infection and mortality varied according to facility size in 965 long-term care homes (LTCHs) in Catalonia during March and April 2020. We measured LTCH size by the number of authorised beds. Outcomes were COVID-19 infection (at least one COVID-19 case in an LTCH) and COVID-19 mortality. Risks of these were estimated with logistic regression and hurdle models. Models were adjusted for county COVID-19 incidence and population, and LTCH types. Sixty-five per cent of the LTCHs were infected by COVID-19. We found a strong association between COVID-19 infection and LTCH size in the adjusted analysis (from 45% in 10-bed homes to 97.5% in those with over 150 places). The average COVID-19 mortality in all LTCHs was 6.8% (3887 deaths) and 9.2% among the COVID-19-infected LTCHs. Very small and large homes had higher COVID-19 mortality, whereas LTCHs with 30 to 70 places had the lowest level. COVID-19 mortality sharply increased with LTCH size in counties with a cumulative incidence of COVID-19 which was higher than 250/100,000, except for very small homes, but slightly decreased with LTCH size when the cumulative incidence of COVID-19 was lower. To prevent infection and preserve life, the optimal size of an LTCH should be between 30 and 70 places.

Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations.

Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.

Effects of Meteorological Factors and Air Pollutants on COVID-19 Transmission under the Action of Control Measures.

At present, COVID-19 is still spreading, and its transmission patterns and the main factors that affect transmission behavior still need to be thoroughly explored. To this end, this study collected the cumulative confirmed cases of COVID-19 in China by 8 April 2020. Firstly, the spatial characteristics of the COVID-19 transmission were investigated by the spatial autocorrelation method. Then, the factors affecting the COVID-19 incidence rates were analyzed by the generalized linear mixed effect model (GLMMs) and geographically weighted regression model (GWR). Finally, the geological detector (GeoDetector) was introduced to explore the influence of interactive effects between factors on the COVID-19 incidence rates. The results showed that: (1) COVID-19 had obvious spatial aggregation. (2) The control measures had the largest impact on the COVID-19 incidence rates, which can explain the difference of 34.2% in the COVID-19 incidence rates, while meteorological factors and pollutant factors can only explain the difference of 1% in the COVID-19 incidence rates. It explains that some of the literature overestimates the impact of meteorological factors on the spread of the epidemic. (3) The influence of meteorological factors was stronger than that of air pollution factors, and the interactive effects between factors were stronger than their individual effects. The interaction between relative humidity and NO2 was stronger. The results of this study will provide a reference for further prevention and control of COVID-19.

The relationship between hydroxychloroquine plasma concentration and COVID-19 outcomes in rheumatoid arthritis patients in Saudi Arabia.

Background: The drug hydroxychloroquine (HCQ) is widely used to treat rheumatoid arthritis (RA) and has been repurposed for the treatment of COVID-19. This study aims to determine whether HCQ concentration levels in individuals with RA alter the incidence of COVID-19 or its complications. Methods: We collected plasma samples from 13 individuals with confirmed rheumatoid arthritis (RA) to measure HCQ concentration levels. The study included individuals at least 18 years old who had been taking HCQ for at least six months at daily doses ranging from 200 to 400 mg. Results: The study enrolled a total of 13 RA patients. All patients were chronic HCQ users. Among the 13 patients, 7 patients were receiving HCQ at a dose of 200 mg per day, and 6 patients were receiving HCQ at a dose of 400 mg per day. COVID-19 confirmed cases accounted for approximately 46% of all patients. Half of the infected patients (n = 3) were taking a daily dose of 200 mg daily, while the other half were taking 400 mg daily. COVID-19 symptoms ranged from mild to moderate, and the intensity of the symptoms was not severe enough to necessitate hospitalization. COVID-19 symptoms in RA patients included headache, fever, fatigue, dry cough, and loss of taste or smell. Conclusions: Our findings indicated that there was no correlation between HCQ concentrations in rheumatoid arthritis patients and the occurrence of COVID-19 or its complications.

The Impact of Immunization with Anti-Coronavirus Vaccines on the Incidence of COVID-19 in Employees of a Large Tuberculosis Institution in Moscow

Relevance. Employees of a TB facility are a high-risk group for the incidence of COVID-19 due to their involvement in the detection and treatment of a new coronavirus infection, so vaccination of staff should play a significant role in their protection against a new coronavirus infection. Aim. Analyze the incidence of COVID-19 in employees of a large TB medical organization in a big city before and after mass immunization with anti-coronavirus vaccines. Materials & Methods. An analysis was made of the incidence of a new coronavirus infection COVID-19 among employees of the Moscow Research and Clinical Center for Tuberculosis Control during April 1, 2020–September 30, 2021, considering two periods of nine months in 2020 (2771 employees) and 2021 (2845 employees) and taking into account the data on the implementation of the first and second vaccinations carried out during the study period. Calculation of the average weekly and annual incidence per 1000 employees was carried out taking into account the different time spent by employees "at risk of getting sick". The incidence rate was calculated both for the entire study period as a whole and for weeks of high risk of COVID-19 incidence in the population of Moscow with an indicator of 500 or more per 100,000 population. Results. A comparative analysis of the incidence of COVID-19, registered from April 1, 2020 to October 1, 2021, was carried out among the average number of 2808 employees of the leading anti-TB institution in Moscow, taking into account vaccination. During the period under review, a total of 35.5% of employees in the institution fell ill and the annual incidence of staff was 177.4 per 1000 employees. 5.7% [95% CI 4.4–7.4%] of previously ill employees had a recurrence of the disease. Being unvaccinated until September 2020 and limitedly vaccinated until July 2021, the staff of the Center was massively immunized from July to August 2021 – up to 86.0% of the institution's staff by the end of the observation period. Based on the calculation of the weekly number of disease cases and of not yet ill persons among fully vaccinated, vaccinated with one drug, not vaccinated and previously ill, the incidence in these groups was compared, taking into account the time at risk of disease before a new case of COVID-19 was registered. For periods of high monthly incidence of the city's population (above 500 per 100 thousand), the annual notification rate of the unvaccinated was 2.8 times higher than that of the fully vaccinated (408.2 and 144.0 per 1000 people, RR = 2.8 [95% CI: 2.0–4.0]). The notification rate among those vaccinated with only one component of the two-component vaccine was 1.5 times higher than among those who were not vaccinated (271.5 and 409.2 per 1000 people. RR = 1.5 [95% CI: 1.04–2.2]). The probability of getting sick in fully vaccinated people was significantly higher than in those who previous infected with SARS-CoV-2 (144.0 and 78.0 per 1000 people, RR = 1.9 [95% CI: 1.1–3.1]). Conclusions. The obvious effectiveness of vaccination has been confirmed, including among the personnel of medical organizations directly involved in the fight against a new coronavirus infection. © Belilovsky EM, et al.

A Population-Level Analysis of the Protective Effects of Androgen Deprivation Therapy Against COVID-19 Disease Incidence and Severity.

Background: The incidence and severity of coronavirus disease 19 (COVID-19) is substantially higher in men. Sex hormones may be a potential mechanism for differences in COVID-19 outcome in men and women. We hypothesized that men treated with androgen deprivation therapy (ADT) have lower incidence and severity of COVID-19. Methods: We conducted an observational study of male Veterans treated in the Veterans Health Administration from February 15th to July 15th, 2020. We developed a propensity score model to predict the likelihood to undergo Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing. We performed multivariable logistic regression modeling adjusted with inverse probability weighting to examine the relationship between ADT and COVID-19 incidence. We conducted logistic regression analysis among COVID-19 patients to test the association between ADT and COVID-19 severity. Results: We identified a large cohort of 246,087 VA male patients who had been tested for SARS-CoV-2, of whom 3,057 men were exposed to ADT, and 36,096 men with cancer without ADT. Of these, 295 ADT patients and 2,427 cancer patients not on ADT had severe COVID-19 illness. In the primary, propensity-weighted comparison of ADT patients to cancer patients not on ADT, ADT was associated with decreased likelihood of testing positive for SARS-CoV-2 (adjusted OR, 0.88 [95% CI, 0.81-0.95]; p = 0.001). Furthermore, ADT was associated with fewer severe COVID-19 outcomes (OR 0.72 [95% CI 0.53-0.96]; p = 0.03). Conclusion: ADT is associated with reduced incidence and severity of COVID-19 amongst male Veterans. Testosterone and androgen receptor signaling may confer increased risk for SARS-CoV-2 infection and contribute to severe COVID-19 pathophysiology in men.

Urbanization and COVID‐19 incidence: A cross‐country investigation: Papers and Proceedings

This paper investigates the determinants of the diffusion and intensity of the COVID‐19 at the country level, focusing on the role played by urban agglomeration, measured using three urban variables: percentage of the urban population, population density, and primacy. We estimate the influence of urban agglomeration on two outcome variables: cumulative number of cases and deaths per 100,000 inhabitants up to 31 December 2020, using both parametric and semiparametric models. We also explore possible spatial effects. The non‐linear effects of the urban variables on the intensity of the disease reveal non‐monotonous relationships, suggesting that it is the size of the urban system that is linked to a stronger incidence.Alternate :Este artículo investiga los determinantes de la difusión y la intensidad de COVID‐19 a nivel de país, centrándose en el papel que desempeña la aglomeración urbana, medida a través de tres variables urbanas: el porcentaje de población urbana, la densidad de población y la primacía. Se utilizaron modelos paramétricos y semiparamétricos para estimar la influencia de la aglomeración urbana en dos variables de resultado: el número acumulado de casos y de muertes por 100.000 habitantes hasta el 31 de diciembre de 2020. También se exploraron los posibles efectos espaciales. Los efectos no lineales de las variables urbanas sobre la intensidad de la enfermedad revelaron relaciones no monótonas, lo que sugiere que el tamaño del sistema urbano es lo que está vinculado a una mayor incidencia.Alternate :抄録本稿では、都市集積が果たす役割に焦点を当てて、3つの都市変数〔urban variable:都市人口の割合(パーセンテージ)、人口密度、首座都市性(primacy)〕を用いて測定して、国レベルでのCOVID‐19の拡散とその強度の決定要因を調査する。パラメトリックモデル及びセミパラメトリックモデルの両方を用いて、2020年12月31日までの住民10万人当たりの累積症例数と死亡数の2つの結果変数に対する都市集積の影響を推定した。また、空間効果も推定した。疾患の強度に対する都市変数の非線形効果は非単調関係を示したことから、発生率をより大きくするのは都市システムのサイズであることが示唆された。

Exposure-lag response of air temperature on COVID-19 incidence in twelve Italian cities: A meta-analysis.

The exposure-lag response of air temperature on daily COVID-19 incidence is unclear and there have been concerns regarding the robustness of previous studies. Here we present an analysis of high spatial and temporal resolution using the distributed lag non-linear modelling (DLNM) framework. Utilising nearly two years' worth of data, we fit statistical models to twelve Italian cities to quantify the delayed effect of air temperature on daily COVID-19 incidence, accounting for several categories of potential confounders (meteorological, air quality and non-pharmaceutical interventions). Coefficients and covariance matrices for the temperature term were then synthesised using random effects meta-analysis to yield pooled estimates of the exposure-lag response with effects presented as the relative risk (RR) and cumulative RR (RRcum). The cumulative exposure response curve was non-linear, with peak risk at 15.1 °C and declining risk at progressively lower and higher temperatures. The lowest RRcum at 0.2 °C is 0.72 [0.56,0.91] times that of the highest risk. Due to this non-linearity, the shape of the lag response curve necessarily varied by temperature. This work suggests that on a given day, air temperature approximately 15 °C maximises the incidence of COVID-19, with the effects distributed in the subsequent ten days or more.

COVID-19 Infection and Incidence of Myocarditis: A Multi-Site Population-Based Propensity Score-Matched Analysis.

Background Cardiovascular complications from COVID-19 include myocarditis, acute myocardial infarction, heart failure, and others. Population-level data is lacking about the relationship between COVID-19 and cardiovascular complications; therefore, we conducted a study to examine the incidence of myocarditis, acute myocardial infarction (AMI), heart failure (HF) after COVID-19 infection. Methods Retrospective cohort study using de-identified data from 50 health systems across the United States. Cohort groups were created using patients ≥18 who were admitted to hospitals for respiratory illness with COVID-19 in 2020 and respiratory illness without COVID-19 for 2020 and 2019. There were 107,699 patients with COVID-19, 77,499 patients with respiratory illness in 2020, and 112,898 patients in 2019. The COVID-19 group was matched to each respiratory illness group by propensity score. Patients with prior specific cardiovascular events such as myocarditis, AMI, HF were excluded. The primary outcome was myocarditis, and secondary outcomes were AMI and HF. Results In the COVID-19 group, 79 (0.12%) patients had new-onset myocarditis compared to 29 (0.04%) patients in the non-COVID-19 control (Pneumonia/flu) group Odd's Ratio (OR), (OR 2.73, CI 95%, 1.78-4.18). In the COVID-19 group, 1512 patients developed HF compared to 2,659 patients in the non-COVID-19 group (OR 0.49, CI 95%, 0.46-0.52). 1125 patients in COVID-19 group had AMI compared to 1243 patients in non-COVID-19 group (OR 0.87, CI 95%, 0.80-0.94). Conclusion COVID-19 was associated with a 2-3-fold higher risk of myocarditis. Unexpectedly, lower rates of HF diagnosis reflect challenges faced due to the severity of lung disease leading to obscuring physical exam findings required for HF diagnosis and early mortality before a diagnosis of HF was made.

The impact of confinement on orthopaedic and trauma surgical activity

Introduction: Le 16 mars 2020, devant l’état d'urgence sanitaire décrété en France, le gouvernement a imposé des mesures de confinement dont l'impact sur l'activité de chirurgie orthopédique et traumatologique reste à démontrer. L'hypothèse de cette étude était que le confinement a diminué l'activité chirurgicale orthopédique et traumatologique. L'objectif principal était d’évaluer l'activité chirurgicale d'orthopédie et de traumatologie en période de confinement et de la comparer à l'activité hors confinement. Matériels & méthodes: Il s'agissait d'une étude rétrospective, monocentrique, observationnelle et comparative d'une cohorte continue de patients inclus pendant la période de confinement du 16 mars au 11 mai 2020. Cette cohorte a été comparée à un groupe de patients inclus de manière rétrospective sur la même période hors confinement l'année précédente du 16 mars au 11 mai 2019. Le critère de jugement principal était le taux d'incidence de l'activité chirurgicale en 2020 versus 2019 sur une période identique. Le critère secondaire était l'analyse des traumatismes recensés. Résultats: Le nombre de patients opérés était significativement diminué en période de confinement: 194 patients inclus en 2020 soit une incidence de 57 pour 100 000 habitants contre 772 patients inclus en 2019 soit une incidence de 227 pour 100 000 habitants;p < 0,001. L'activité chirurgicale d'orthopédie programmée passait d'un taux d'incidence de 147 en 2019 à 5 en 2020 pour 100 000 habitants (p < 0,001). L'activité chirurgicale de traumatologie passait d'un taux d'incidence de 80 en 2019 à 50 en 2020 pour 100 000 habitants (p: NS). Nous retrouvions une augmentation significative des patients de plus de 65 ans pendant le confinement, 70 % contre 61 % en 2019;p = 0,04. Le taux de fractures du col du fémur était significativement augmenté pendant le confinement, 48,5 % contre 39,3 % en 2019;p = 0,03. La chirurgie dégénérative était significativement diminuée pendant le confinement (p < 0,001). Discussion: Cette étude montre que l'activité chirurgicale d'orthopédie et de traumatologie a été significativement diminué par le confinement, avec une différence d'incidence de 170 pour 100 000 habitants, confirmant ainsi l'hypothèse des auteurs. Cette diminution est due à la fois à l'arrêt de l'orthopédie programmée et à la diminution de 40 % du nombre de patients traumatisés. En période de confinement, le pourcentage de patients âgés de plus de 65 ans victime d'une fracture a significativement augmenté. Conclusion: Le confinement a eu un impact significatif sur l'activité de chirurgie orthopédique et traumatologique. Niveau de preuve: III;comparative et rétrospective. © 2021 Elsevier Masson SAS