Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 25
Filter
2.
Dtsch Arztebl Int ; 119(11): 179-187, 2022 03 18.
Article in English | MEDLINE | ID: covidwho-2308266

ABSTRACT

BACKGROUND: Numerous studies have reported an increase in mental disorders during the COVID-19 pandemic, but the exact reasons for this development are not well understood. In this study we investigate whether pandemic-related occupational and financial changes (e.g., reduced working hours, working from home, financial losses) were associated with increased symptoms of depression and anxiety compared with the situation before the pandemic. METHODS: We analyzed data from the German National Cohort (NAKO) Study. Between May and November 2020, 161 849 study participants answered questions on their mental state and social circumstances. Their responses were compared with data from the baseline survey before the pandemic (2014-2019). Linear fixed-effects models were used to determine whether individual changes in the severity of symptoms of depression (PHQ-9) or anxiety (GAD-7) were associated with occupational/ financial changes (controlling for various covariates). RESULTS: The prevalence of moderate or severe symptoms of depression and anxiety increased by 2.4% and 1.5%, respectively, during the COVID-19 pandemic compared with the preceding years. The mean severity of the symptoms rose slightly. A pronounced increase in symptoms was observed among those who became unemployed during the pandemic (+ 1.16 points on the depression scale, 95% confidence interval [0.91; 1.41], range 0-27). Increases were also seen for reduced working hours with no short-time allowance, increased working hours, working from home, insecurity regarding employment, and financial strain. The deterioration in mental health was largely statistically explained by the occupational and financial changes investigated in the model. CONCLUSION: Depressive symptoms and anxiety disorders increased slightly in the study population during the first year of the COVID-19 pandemic. Occupational and financial difficulties were an essential contributory factor. These strains should be taken into account both in the care of individual patients and in the planning of targeted prevention measures.


Subject(s)
COVID-19 , Mental Disorders , Anxiety/epidemiology , COVID-19/epidemiology , Depression/diagnosis , Depression/epidemiology , Humans , Mental Disorders/epidemiology , Pandemics , SARS-CoV-2
3.
Econ Hum Biol ; 49: 101198, 2023 04.
Article in English | MEDLINE | ID: covidwho-2240357

ABSTRACT

Decisions on public health measures to contain a pandemic are often based on parameters such as expected disease burden and additional mortality due to the pandemic. Both pandemics and non-pharmaceutical interventions to fight pandemics, however, produce economic, social, and medical costs. The costs are, for example, caused by changes in access to healthcare, social distancing, and restrictions on economic activity. These factors indirectly influence health outcomes in the short- and long-term perspective. In a narrative review based on targeted literature searches, we develop a comprehensive perspective on the concepts available as well as the challenges of estimating the overall disease burden and the direct and indirect effects of COVID-19 interventions from both epidemiological and economic perspectives, particularly during the early part of a pandemic. We review the literature and discuss relevant components that need to be included when estimating the direct and indirect effects of the COVID-19 pandemic. The review presents data sources and different forms of death counts, and discusses empirical findings on direct and indirect effects of the pandemic and interventions on disease burden as well as the distribution of health risks.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , SARS-CoV-2 , Public Health , Cost of Illness
4.
Eur J Epidemiol ; 38(1): 39-58, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-2234929

ABSTRACT

Current estimates of pandemic SARS-CoV-2 spread in Germany using infectious disease models often do not use age-specific infection parameters and are not always based on age-specific contact matrices of the population. They also do usually not include setting- or pandemic phase-based information from epidemiological studies of reported cases and do not account for age-specific underdetection of reported cases. Here, we report likely pandemic spread using an age-structured model to understand the age- and setting-specific contribution of contacts to transmission during different phases of the COVID-19 pandemic in Germany. We developed a deterministic SEIRS model using a pre-pandemic contact matrix. The model was optimized to fit age-specific SARS-CoV-2 incidences reported by the German National Public Health Institute (Robert Koch Institute), includes information on setting-specific reported cases in schools and integrates age- and pandemic period-specific parameters for underdetection of reported cases deduced from a large population-based seroprevalence studies. Taking age-specific underreporting into account, younger adults and teenagers were identified in the modeling study as relevant contributors to infections during the first three pandemic waves in Germany. For the fifth wave, the Delta to Omicron transition, only age-specific parametrization reproduces the observed relative and absolute increase in pediatric hospitalizations in Germany. Taking into account age-specific underdetection did not change considerably how much contacts in schools contributed to the total burden of infection in the population (up to 12% with open schools under hygiene measures in the third wave). Accounting for the pandemic phase and age-specific underreporting is important to correctly identify those groups of the population in which quarantine, testing, vaccination, and contact-reduction measures are likely to be most effective and efficient. Age-specific parametrization is also highly relevant to generate informative age-specific output for decision makers and resource planers.


Subject(s)
COVID-19 , SARS-CoV-2 , Adult , Adolescent , Humans , Child , COVID-19/epidemiology , Pandemics , Seroepidemiologic Studies , Age Factors , Germany/epidemiology
5.
Clin Infect Dis ; 2022 Jun 19.
Article in English | MEDLINE | ID: covidwho-2237813

ABSTRACT

BACKGROUND: The rapid emergence of the omicron variant and its large number of mutations led to its classification as a variant of concern (VOC) by the WHO. Subsequently, omicron evolved into distinct sublineages (e.g. BA1 and BA2), which currently represent the majority of global infections. Initial studies of the neutralizing response towards BA1 in convalescent and vaccinated individuals showed a substantial reduction. METHODS: We assessed antibody (IgG) binding, ACE2 (Angiotensin-Converting Enzyme 2) binding inhibition, and IgG binding dynamics for the omicron BA1 and BA2 variants compared to a panel of VOC/VOIs, in a large cohort (n = 352) of convalescent, vaccinated, and infected and subsequently vaccinated individuals. RESULTS: While omicron was capable efficiently binding to ACE2, antibodies elicited by infection or immunization showed reduced binding capacities and ACE2 binding inhibition compared to WT. Whereas BA1 exhibited less IgG binding compared to BA2, BA2 showed reduced inhibition of ACE2 binding. Among vaccinated samples, antibody binding to omicron only improved after administration of a third dose. CONCLUSION: omicron BA1 and BA2 can still efficiently bind to ACE2, while vaccine/infection-derived antibodies can bind omicron. The extent of the mutations within both variants prevent a strong inhibitory binding response. As a result, both omicron variants are able to evade control by pre-existing antibodies.

6.
PLoS Med ; 19(12): e1003913, 2022 12.
Article in English | MEDLINE | ID: covidwho-2196852

ABSTRACT

BACKGROUND: School-level infection control measures in Germany during the early Coronavirus Disease 2019 (COVID-19) pandemic differed across the 16 federal states and lacked a dependable evidence base, with available evidence limited to regional data restricted to short phases of the pandemic. This study aimed to assess the (a) infection risks in students and staff; (b) transmission risks and routes in schools; (c) effects of school-level infection control measures on school and population infection dynamics; and (d) contribution of contacts in schools to population cases. METHODS AND FINDINGS: For this retrospective observational study, we used German federal state (NUTS-2) and county (NUTS-3) data from public health and education agencies from March 2020 to April 2022. We assessed (a) infection risk as cumulative risk and crude risk ratios and (b) secondary attack rates (SARs) with 95% confidence interval (CI). We used (c) multiple regression analysis for the effects of infection control measures such as reduced attendance, mask mandates, and vaccination coverage as absolute reduction in case incidence per 100,000 inhabitants per 14 days and in percentage relative to the population, and (d) infection dynamic modelling to determine the percentage contribution of school contacts to population cases. We included (a) nationwide NUTS-2 data from calendar weeks (W) 46-50/2020 and W08/2021-W15/2022 with 3,521,964 cases in students and 329,283 in teachers; (b) NUTS-3 data from W09-25/2021 with 85,788 student and 9,427 teacher cases; and (c) detailed data from 5 NUTS-3 regions from W09/2020 to W27/2021 with 12,814 cases (39% male, 37% female; median age 14, range 5 to 63), 43,238 contacts and 4,165 secondary cases for students (for teachers, 14,801 [22% male, 50% female; median age 39, range 16 to 75], 5,893 and 472). Infection risk (a) for students and teachers was higher than the population risk in all phases of normal presence class and highest in the early 2022 omicron wave with 30.6% (95% CI 30.5% to 32.6%) of students and 32.7% (95% CI 32.6% to 32.8%) of teachers infected in Germany. SARs (b) for students and staff were below 5% in schools throughout the study period, while SARs in households more than doubled from 13.8% (95% CI 10.6% to 17.6%) W21-39/2020 to 28.7% (95% CI 27% to 30.4%) in W08-23/2021 for students and 10.9% (95% CI 7% to 16.5%) to 32.7% (95% CI 28.2% to 37.6%) for staff. Most contacts were reported for schools, yet most secondary cases originated in households. In schools, staff predominantly infected staff. Mandatory surgical mask wearing during class in all schools was associated with a reduction in the case incidence of students and teachers (c), by 56/100,000 persons per 14 days (students: 95% CI 47.7 to 63.4; teachers: 95% CI 39.6 to 71.6; p < 0.001) and by 29.8% (95% CI 25% to 35%, p < 0.001) and 24.3% (95% CI 13% to 36%, p < 0.001) relative to the population, respectively, as were reduced attendance and higher vaccination coverage. The contribution of contacts in schools to population cases (d) was 2% to 20%, lowest during school closures/vacation and peaked during normal presence class intervals, with the overall peak early during the omicron wave. Limitations include underdetection, misclassification of contacts, interviewer/interviewee dependence of contact-tracing, and lack of individual-level confounding factors in aggregate data regression analysis. CONCLUSION: In this study, we observed that open schools under hygiene measures and testing strategies contributed up to 20% of population infections during the omicron wave early 2022, and as little as 2% during vacations/school closures; about a third of students and teachers were infected during the omicron wave in early 2022 in Germany. Mandatory mask wearing during class in all school types and reduced attendance models were associated with a reduced infection risk in schools.


Subject(s)
COVID-19 , Female , Male , Humans , Adolescent , Adult , COVID-19/epidemiology , Educational Status , Schools , Students , Germany/epidemiology
7.
Sci Rep ; 12(1): 19858, 2022 Nov 18.
Article in English | MEDLINE | ID: covidwho-2133587

ABSTRACT

SARS-CoV-2 variants accumulating immune escape mutations provide a significant risk to vaccine-induced protection against infection. The novel variant of concern (VoC) Omicron BA.1 and its sub-lineages have the largest number of amino acid alterations in its Spike protein to date. Thus, they may efficiently escape recognition by neutralizing antibodies, allowing breakthrough infections in convalescent and vaccinated individuals in particular in those who have only received a primary immunization scheme. We analyzed neutralization activity of sera from individuals after vaccination with all mRNA-, vector- or heterologous immunization schemes currently available in Europe by in vitro neutralization assay at peak response towards SARS-CoV-2 B.1, Omicron sub-lineages BA.1, BA.2, BA.2.12.1, BA.3, BA.4/5, Beta and Delta pseudotypes and also provide longitudinal follow-up data from BNT162b2 vaccinees. All vaccines apart from Ad26.CoV2.S showed high levels of responder rates (96-100%) towards the SARS-CoV-2 B.1 isolate, and minor to moderate reductions in neutralizing Beta and Delta VoC pseudotypes. The novel Omicron variant and its sub-lineages had the biggest impact, both in terms of response rates and neutralization titers. Only mRNA-1273 showed a 100% response rate to Omicron BA.1 and induced the highest level of neutralizing antibody titers, followed by heterologous prime-boost approaches. Homologous BNT162b2 vaccination, vector-based AZD1222 and Ad26.CoV2.S performed less well with peak responder rates of 48%, 56% and 9%, respectively. However, Omicron responder rates in BNT162b2 recipients were maintained in our six month longitudinal follow-up indicating that individuals with cross-protection against Omicron maintain it over time. Overall, our data strongly argue for booster doses in individuals who were previously vaccinated with BNT162b2, or a vector-based primary immunization scheme.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Neutralization Tests , Antibodies, Viral , COVID-19 Vaccines , RNA, Messenger , Ad26COVS1 , BNT162 Vaccine , COVID-19/prevention & control , ChAdOx1 nCoV-19 , Vaccination
8.
BMC Infect Dis ; 22(1): 859, 2022 Nov 17.
Article in English | MEDLINE | ID: covidwho-2139175

ABSTRACT

BACKGROUND: Lyme borreliosis (LB) is the most common tick-borne infectious disease in the northern hemisphere. The diagnosis of LB is usually made by clinical symptoms and subsequently supported by serology. In Europe, a two-step testing consisting of an enzyme-linked immunosorbent assay (ELISA) and an immunoblot is recommended. However, due to the low sensitivity of the currently available tests, antibody detection is sometimes inaccurate, especially in the early phase of infection, leading to underdiagnoses. METHODS: To improve upon Borrelia diagnostics, we developed a multiplex Borrelia immunoassay (Borrelia multiplex), which utilizes the new INTELLIFLEX platform, enabling the simultaneous dual detection of IgG and IgM antibodies, saving further time and reducing the biosample material requirement. In order to enable correct classification, the Borrelia multiplex contains eight antigens from the five human pathogenic Borrelia species known in Europe. Six antigens are known to mainly induce an IgG response and two antigens are predominant for an IgM response. RESULTS: To validate the assay, we compared the Borrelia multiplex to a commercial bead-based immunoassay resulting in an overall assay sensitivity of 93.7% (95% CI 84.8-97.5%) and a specificity of 96.5% (95%CI 93.5-98.1%). To confirm the calculated sensitivity and specificity, a comparison with a conventional 2-step diagnostics was performed. With this comparison, we obtained a sensitivity of 95.2% (95% CI 84.2-99.2%) and a specificity of 93.0% (95% CI 90.6-94.7%). CONCLUSION: Borrelia multiplex is a highly reproducible cost- and time-effective assay that enables the profiling of antibodies against several individual antigens simultaneously.


Subject(s)
Borrelia , Lyme Disease , Humans , Antibodies, Bacterial , Serologic Tests/methods , Immunoglobulin G , Lyme Disease/diagnosis , Immunoglobulin M
9.
Front Immunol ; 13: 1004045, 2022.
Article in English | MEDLINE | ID: covidwho-2080154

ABSTRACT

Haemodialysis patients respond poorly to vaccination and continue to be at-risk for severe COVID-19. Therefore, dialysis patients were among the first for which a fourth COVID-19 vaccination was recommended. However, targeted information on how to best maintain immune protection after SARS-CoV-2 vaccinations in at-risk groups for severe COVID-19 remains limited. We provide, to the best of our knowledge, for the first time longitudinal vaccination response data in dialysis patients and controls after a triple BNT162b2 vaccination and in the latter after a subsequent fourth full-dose of mRNA-1273. We analysed systemic and mucosal humoral IgG responses against the receptor-binding domain (RBD) and ACE2-binding inhibition towards variants of concern including Omicron and Delta with multiplex-based immunoassays. In addition, we assessed Spike S1-specific T-cell responses by interferon γ release assay. After triple BNT162b2 vaccination, anti-RBD B.1 IgG and ACE2 binding inhibition reached peak levels in dialysis patients, but remained inferior compared to controls. Whilst we detected B.1-specific ACE2 binding inhibition in 84% of dialysis patients after three BNT162b2 doses, binding inhibition towards the Omicron variant was only detectable in 38% of samples and declining to 16% before the fourth vaccination. By using mRNA-1273 as fourth dose, humoral immunity against all SARS-CoV-2 variants tested was strongly augmented with 80% of dialysis patients having Omicron-specific ACE2 binding inhibition. Modest declines in T-cell responses in dialysis patients and controls after the second vaccination were restored by the third BNT162b2 dose and significantly increased by the fourth vaccination. Our data support current advice for a four-dose COVID-19 immunisation scheme for at-risk individuals such as haemodialysis patients. We conclude that administration of a fourth full-dose of mRNA-1273 as part of a mixed mRNA vaccination scheme to boost immunity and to prevent severe COVID-19 could also be beneficial in other immune impaired individuals. Additionally, strategic application of such mixed vaccine regimens may be an immediate response against SARS-CoV-2 variants with increased immune evasion potential.


Subject(s)
COVID-19 , Viral Vaccines , Mice , Animals , Humans , Immunity, Humoral , SARS-CoV-2 , 2019-nCoV Vaccine mRNA-1273 , BNT162 Vaccine , COVID-19/prevention & control , Angiotensin-Converting Enzyme 2 , COVID-19 Vaccines , Mice, Inbred BALB C , Vaccination , Immunoglobulin G , Renal Dialysis , RNA, Messenger
10.
Scand J Work Environ Health ; 48(7): 588-590, 2022 Sep 01.
Article in English | MEDLINE | ID: covidwho-2056012

ABSTRACT

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

11.
BMC Infect Dis ; 22(1): 500, 2022 May 27.
Article in English | MEDLINE | ID: covidwho-1892180

ABSTRACT

BACKGROUND: There remain gaps in quantifying mortality risk among individuals co-infected with chronic hepatitis B (HBV) and human immunodeficiency virus (HIV) in sub-Saharan African contexts. Among a cohort of HIV-positive individuals in Rwanda, we estimate the difference in time-to mortality between HBV-positive (HIV/HBV co-infected) and HBV-negative (HIV mono-infected) individuals. METHODS: Using a dataset of HIV-infected adults screened for hepatitis B surface antigen (HBsAg) from January to June 2016 in Rwanda, we performed time-to-event analysis from the date of HBsAg results until death or end of study (31 December 2019). We used the Kaplan-Meier method to estimate probability of survival over time and Cox proportional hazard models to adjust for other factors associated with mortality. RESULTS: Of 21,105 available entries, 18,459 (87.5%) met the inclusion criteria. Mean age was 42.3 years (SD = 11.4) and 394 (2.1%) died during follow-up (mortality rate = 45.7 per 100,000 person-months, 95% confidence interval (CI) 41.4-50.4) Mortality rate ratio for co-infection was 1.7, 95% CI 1.1-2.6, however, Cox regression analysis did not show any association with mortality between compared groups. The adjusted analysis of covariates stratified by co-infection status showed that males, residing outside of the capital Kigali, drinking alcohol, WHO-HIV-clinical stage 3 and 4 were associated with increased mortality in this HIV cohort. CONCLUSIONS: HBV infection does not significantly influence mortality among HIV-infected individuals in Rwanda. The current cohort is likely to have survived a period of high-risk exposure to HBV and HIV mortality and limited health care until their diagnosis.


Subject(s)
Coinfection , HIV Infections , Hepatitis B, Chronic , Adult , Coinfection/complications , HIV Infections/complications , Hepatitis B Surface Antigens , Hepatitis B virus , Hepatitis B, Chronic/complications , Humans , Male , Rwanda/epidemiology
12.
Scand J Work Environ Health ; 48(6): 446-456, 2022 09 01.
Article in English | MEDLINE | ID: covidwho-1879594

ABSTRACT

OBJECTIVE: The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020). METHODS: We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship. RESULTS: The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72). CONCLUSIONS: The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Germany/epidemiology , Humans , Occupations , SARS-CoV-2
13.
Stud Health Technol Inform ; 294: 669-673, 2022 May 25.
Article in English | MEDLINE | ID: covidwho-1865432

ABSTRACT

In recent years, software has evolved from being static, closed source, proprietary products to being dynamic, open source, ecosystems contributing to the global good. To this end, the open source software (OSS) solution and global good, Surveillance Outbreak Response Management and Analysis System (SORMAS), rapidly adjusted to the demands of the Coronavirus disease 2019 (COVID-19) outbreak by introducing a COVID-19 module. This allowed countries that were already making use of the software as part of their public health surveillance infrastructure to make use of the new module in order to respond to the pandemic. New countries in continental Europe, most notably Germany, Switzerland, Liechtenstein and France subsequently chose to adopt the software for public health surveillance purposes for the first time during 2020, requiring additional adaptations to meet local needs. As a result, in this paper, we aim to gain a better understanding of how rapidly SORMAS was adapted to meet global needs by analyzing the SORMAS COVID-19 module introduction timeline, as well as the overall development activity of the software during 2020 and 2021 in response to the pandemic. Favorable initial feature response times in combination with development scale-up possibilities speak to some of the potential advantages of implementing global good OSS tools such as SORMAS for public health surveillance, in response to an emergency. Overall, SORMAS serves as proof of concept for developing a global good OSS solution on an international scale.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Ecosystem , Europe/epidemiology , Humans , Software
14.
JMIR Public Health Surveill ; 8(5): e34438, 2022 05 31.
Article in English | MEDLINE | ID: covidwho-1834169

ABSTRACT

BACKGROUND: The Surveillance Outbreak Response Management and Analysis System (SORMAS) contains a management module to support countries in their epidemic response. It consists of the documentation, linkage, and follow-up of cases, contacts, and events. To allow SORMAS users to visualize data, compute essential surveillance indicators, and estimate epidemiological parameters from such network data in real-time, we developed the SORMAS Statistics (SORMAS-Stats) application. OBJECTIVE: This study aims to describe the essential visualizations, surveillance indicators, and epidemiological parameters implemented in the SORMAS-Stats application and illustrate the application of SORMAS-Stats in response to the COVID-19 outbreak. METHODS: Based on findings from a rapid review and SORMAS user requests, we included the following visualization and estimation of parameters in SORMAS-Stats: transmission network diagram, serial interval (SI), time-varying reproduction number R(t), dispersion parameter k, and additional surveillance indicators presented in graphs and tables. We estimated SI by fitting lognormal, gamma, and Weibull distributions to the observed distribution of the number of days between symptom onset dates of infector-infectee pairs. We estimated k by fitting a negative binomial distribution to the observed number of infectees per infector. Furthermore, we applied the Markov Chain Monte Carlo approach and estimated R(t) using the incidence data and the observed SI computed from the transmission network data. RESULTS: Using COVID-19 contact-tracing data of confirmed cases reported between July 31 and October 29, 2021, in the Bourgogne-Franche-Comté region of France, we constructed a network diagram containing 63,570 nodes. The network comprises 1.75% (1115/63,570) events, 19.59% (12,452/63,570) case persons, and 78.66% (50,003/63,570) exposed persons, including 1238 infector-infectee pairs and 3860 transmission chains with 24.69% (953/3860) having events as the index infector. The distribution with the best fit to the observed SI data was a lognormal distribution with a mean of 4.30 (95% CI 4.09-4.51) days. We estimated a dispersion parameter k of 21.11 (95% CI 7.57-34.66) and an effective reproduction number R of 0.9 (95% CI 0.58-0.60). The weekly estimated R(t) values ranged from 0.80 to 1.61. CONCLUSIONS: We provide an application for real-time estimation of epidemiological parameters, which is essential for informing outbreak response strategies. The estimates are commensurate with findings from previous studies. The SORMAS-Stats application could greatly assist public health authorities in the regions using SORMAS or similar tools by providing extensive visualizations and computation of surveillance indicators.


Subject(s)
COVID-19 , Communicable Diseases , Basic Reproduction Number , COVID-19/epidemiology , Communicable Diseases/epidemiology , Contact Tracing , Disease Outbreaks , Humans
15.
Emerg Infect Dis ; 28(4): 743-750, 2022 04.
Article in English | MEDLINE | ID: covidwho-1770999

ABSTRACT

Patients undergoing chronic hemodialysis were among the first to receive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinations because of their increased risk for severe coronavirus disease and high case-fatality rates. By using a previously reported cohort from Germany of at-risk hemodialysis patients and healthy donors, where antibody responses were examined 3 weeks after the second vaccination, we assessed systemic cellular and humoral immune responses in serum and saliva 4 months after vaccination with the Pfizer-BioNTech BNT162b2 vaccine using an interferon-γ release assay and multiplex-based IgG measurements. We further compared neutralization capacity of vaccination-induced IgG against 4 SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) by angiotensin-converting enzyme 2 receptor-binding domain competition assay. Sixteen weeks after second vaccination, compared with 3 weeks after, cellular and humoral responses against the original SARS-CoV-2 isolate and variants of concern were substantially reduced. Some dialysis patients even had no detectable B- or T-cell responses.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , BNT162 Vaccine , COVID-19/immunology , COVID-19/prevention & control , COVID-19/virology , COVID-19 Vaccines , Humans , Immunity, Humoral , RNA, Messenger , Renal Dialysis , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/genetics , Vaccination
16.
Informatics in Medicine Unlocked ; : 100931, 2022.
Article in English | ScienceDirect | ID: covidwho-1757426

ABSTRACT

Introduction Epidemiological data collection is often challenged by low response and, in the case of cohorts, poor long-term compliance, i.e. a high drop-out. For the correct recording of incident or recurring health events, that are subject to recall difficulties, gathering of data during the event and immediate response of the participants is crucial. This is especially true when biosampling that catches a transient biological situation like COVID-19 is involved. In addition, emerging research topics (e.g. pandemics like the current SARS-CoV-2) demand a flexible approach regarding content while allowing for complex and varying study designs. To meet these needs, we developed an eResearch system for prospective monitoring and management of incident health events (PIA). Methods Programming PIA focusses on IT security and data protection as well as aiming for a user-friendly and motivating design e.g. through feedback for study participants. The main building blocks of the infrastructure are identical functionalities in web-based, iOS and Android compatible application to strengthen the user acceptance of the participants. The backend consists of services and databases, which are all containerised using Docker containers. All programming is based on the JavaScript ecosystem as this is widely used and well supported. Results PIA offers complete management of observational epidemiological studies with six different roles: PIA administrator, researcher, participant manager, study nurse, consent manager and participant. Each role has a specific interface, so that different functions e.g. implementation of new questionnaires, administration of biosamples or management of participant contacts can be performed by different personae. PIA can be integrated in the IT system of ongoing studies like the German National Cohort but also used as stand-alone system. The software is open source (AGPL3.0): https://github.com/hzi-braunschweig/pia-system. Discussion Despite the abundance of existing Electronic Data Capture Systems (EDC systems), we developed our own generic tool that combines monitoring and management in order to use it for specific applications e.g. in certain pre-existing epidemiological studies or for syndromic surveillance in the current pandemic. Hence, PIA is continuously adapted to emerging requirements. Currently, systematic feedback from users is collected. We aim to improve the user experience of PIA as well as provide further feedback and additional elements like gamification in the future.

17.
Front Immunol ; 13: 828053, 2022.
Article in English | MEDLINE | ID: covidwho-1731780

ABSTRACT

Recent increases in SARS-CoV-2 infections have led to questions about duration and quality of vaccine-induced immune protection. While numerous studies have been published on immune responses triggered by vaccination, these often focus on studying the impact of one or two immunisation schemes within subpopulations such as immunocompromised individuals or healthcare workers. To provide information on the duration and quality of vaccine-induced immune responses against SARS-CoV-2, we analyzed antibody titres against various SARS-CoV-2 antigens and ACE2 binding inhibition against SARS-CoV-2 wild-type and variants of concern in samples from a large German population-based seroprevalence study (MuSPAD) who had received all currently available immunisation schemes. We found that homologous mRNA-based or heterologous prime-boost vaccination produced significantly higher antibody responses than vector-based homologous vaccination. Ad26.CoV2S.2 performance was particularly concerning with reduced titres and 91.7% of samples classified as non-responsive for ACE2 binding inhibition, suggesting that recipients require a booster mRNA vaccination. While mRNA vaccination induced a higher ratio of RBD- and S1-targeting antibodies, vector-based vaccines resulted in an increased proportion of S2-targeting antibodies. Given the role of RBD- and S1-specific antibodies in neutralizing SARS-CoV-2, their relative over-representation after mRNA vaccination may explain why these vaccines have increased efficacy compared to vector-based formulations. Previously infected individuals had a robust immune response once vaccinated, regardless of which vaccine they received, which could aid future dose allocation should shortages arise for certain manufacturers. Overall, both titres and ACE2 binding inhibition peaked approximately 28 days post-second vaccination and then decreased.


Subject(s)
Ad26COVS1/immunology , COVID-19/immunology , Immunity, Humoral/immunology , SARS-CoV-2/growth & development , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Antibody Formation/immunology , Cross-Sectional Studies , Germany , Humans , Seroepidemiologic Studies , Spike Glycoprotein, Coronavirus/immunology , Vaccination/methods
18.
Dtsch Arztebl Int ; 118(48): 824-831, 2021 12 03.
Article in English | MEDLINE | ID: covidwho-1706269

ABSTRACT

BACKGROUND: Until now, information on the spread of SARS-CoV-2 infections in Germany has been based mainly on data from the public health offices. It may be assumed that these data do not include many cases of asymptomatic and mild infection. METHODS: We determined seroprevalence over the course of the pandemic in a sequential, multilocal seroprevalence study (MuSPAD). Study participants were recruited at random in seven administrative districts (Kreise) in Germany from July 2020 onward; each participant was tested at two different times 3-5 months apart. Test findings on blood samples were used to determine the missed-case rate of reported infections, the infection fatality rate (IFR), and the association between seropositivity and demographic, socio-economic, and health-related factors, as well as to evaluate the self-reported results of PCR and antigenic tests. The registration number of this study is DRKS00022335. RESULTS: Among non-vaccinated persons, the seroprevalence from July to December 2020 was 1.3-2.8% and rose between February and May 2021 to 4.1-13.1%. In July 2021, 35% of tested persons in Chemnitz were not vaccinated, and the seroprevalence among these persons was 32.4% (07/2021). The surveillance detection ratio (SDR), i.e., the ratio between the true number of infections estimated from seroprevalence and the actual number or reported infections, varied among the districts included in the study from 2.2 to 5.1 up to December 2020 and from 1.3 to 2.9 up to June 2021, and subsequently declined. The IFR was in the range of 0.8% to 2.4% in all regions except Magdeburg, where a value of 0.3% was calculated for November 2020. A lower educational level was associated with a higher seropositivity rate, smoking with a lower seropositivity rate. On average, 1 person was infected for every 8.5 persons in quarantine. CONCLUSION: Seroprevalence was low after the first wave of the pandemic but rose markedly during the second and third waves. The missed-case rate trended downward over the course of the pandemic.


Subject(s)
COVID-19 , SARS-CoV-2 , Germany/epidemiology , Humans , Pandemics , Seroepidemiologic Studies
19.
JMIR Public Health Surveill ; 7(12): e30106, 2021 12 23.
Article in English | MEDLINE | ID: covidwho-1598120

ABSTRACT

BACKGROUND: Gaining oversight into the rapidly growing number of mobile health tools for surveillance or outbreak management in Africa has become a challenge. OBJECTIVE: The aim of this study is to map the functional portfolio of mobile health tools used for surveillance or outbreak management of communicable diseases in Africa. METHODS: We conducted a scoping review by combining data from a systematic review of the literature and a telephone survey of experts. We applied the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines by searching for articles published between January 2010 and December 2020. In addition, we used the respondent-driven sampling method and conducted a telephone survey from October 2019 to February 2020 among representatives from national public health institutes from all African countries. We combined the findings and used a hierarchical clustering method to group the tools based on their functionalities (attributes). RESULTS: We identified 30 tools from 1914 publications and 45 responses from 52% (28/54) of African countries. Approximately 13% of the tools (4/30; Surveillance Outbreak Response Management and Analysis System, Go.Data, CommCare, and District Health Information Software 2) covered 93% (14/15) of the identified attributes. Of the 30 tools, 17 (59%) tools managed health event data, 20 (67%) managed case-based data, and 28 (97%) offered a dashboard. Clustering identified 2 exceptional attributes for outbreak management, namely contact follow-up (offered by 8/30, 27%, of the tools) and transmission network visualization (offered by Surveillance Outbreak Response Management and Analysis System and Go.Data). CONCLUSIONS: There is a large range of tools in use; however, most of them do not offer a comprehensive set of attributes, resulting in the need for public health workers having to use multiple tools in parallel. Only 13% (4/30) of the tools cover most of the attributes, including those most relevant for response to the COVID-19 pandemic, such as laboratory interface, contact follow-up, and transmission network visualization.


Subject(s)
COVID-19 , Pandemics , Africa/epidemiology , Cluster Analysis , Humans , SARS-CoV-2
20.
EBioMedicine ; 70: 103524, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1356202

ABSTRACT

BACKGROUND: Patients with chronic renal insufficiency on maintenance haemodialysis face an increased risk of COVID-19 induced mortality and impaired vaccine responses. To date, only a few studies have addressed SARS-CoV-2 vaccine elicited immunity in this immunocompromised population. METHODS: We assessed immunogenicity of the mRNA vaccine BNT162b2 in at-risk dialysis patients and characterised systemic cellular and humoral immune responses in serum and saliva using interferon γ release assay and multiplex-based cytokine and immunoglobulin measurements. We further compared binding capacity and neutralization efficacy of vaccination-induced immunoglobulins against emerging SARS-CoV-2 variants Alpha, Beta, Epsilon and Cluster 5 by ACE2-RBD competition assay. FINDINGS: Patients on maintenance haemodialysis exhibit detectable but variable cellular and humoral immune responses against SARS-CoV-2 and variants of concern after a two-dose regimen of BNT162b2. Although vaccination-induced immunoglobulins were detectable in saliva and plasma, both anti-SARS-CoV-2 IgG and neutralization efficacy was reduced compared to a vaccinated non-dialysed control population. Similarly, T-cell mediated interferon γ release after stimulation with SARS-CoV-2 spike peptides was significantly diminished. INTERPRETATION: Quantifiable humoral and cellular immune responses after BNT162b2 vaccination in individuals on maintenance haemodialysis are encouraging, but urge for longitudinal follow-up to assess longevity of immunity. Diminished virus neutralization and interferon γ responses in the face of emerging variants of concern may favour this at-risk population for re-vaccination using modified vaccines at the earliest opportunity. FUNDING: Initiative and Networking Fund of the Helmholtz Association of German Research Centres, EU Horizon 2020 research and innovation program, State Ministry of Baden-Württemberg for Economic Affairs, Labour and Tourism.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/immunology , Immunity, Cellular/immunology , Immunity, Humoral/immunology , Immunogenicity, Vaccine/immunology , SARS-CoV-2/immunology , Vaccines, Synthetic/immunology , Aged , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , BNT162 Vaccine , Female , Humans , Immunoglobulin G/immunology , Male , Middle Aged , Renal Dialysis/methods , Spike Glycoprotein, Coronavirus/immunology , T-Lymphocytes/immunology , Vaccination/methods
SELECTION OF CITATIONS
SEARCH DETAIL