COVID-19 transmission dynamics underlying epidemic waves in Kenya.
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ABSTRACT:
SUBMITTER: Brand SPC
PROVIDER: S-EPMC7612211 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe ongoing coronavirus disease 2019 (COVID-19) pandemic has caused a tremendous health burden and impact on the world economy. The UK Government implemented the biggest lockdown of society during peacetime in British history at the end of March 2020, aiming to contain the rapid spread of the virus. The UK lockdown was maintained for 7 weeks, but the effectiveness of the control measures in suppressing disease transmission remains incompletely understood.MethodsA Bayesian SEIR (susceptible-exposed-infected-removed) epidemiological model was used to rebuild the local transmission dynamics of the spread of COVID-19 in nine regions of England.ResultsThe basic reproduction number (R0) in England was found to be relatively high compared with China. The estimate of the temporally varying effective reproduction number (Rt) suggests that the control measures, especially the forced lockdown, were effective to reduce transmissibility and curb the COVID-19 epidemic. Although the overall incidence rate in the UK has declined, forecasting highlights the possibility of a second epidemic wave in several regions.ConclusionThis study enhances understanding of the current outbreak and the effectiveness of control measures in the UK.
| S-EPMC7757353 | biostudies-literature
Project description:Manuscript describes the daily dynamics of transcriptional responses in whole blood, from acute to convalescent phase, in severe and non-severe COVID-19 patients.
2020-12-31 | E-MTAB-9721 | biostudies-arrayexpress
Project description:India imposed one of the world's strictest population-wide lockdowns on March 25, 2020 for COVID-19. We estimated epidemiological parameters, evaluated the effect of control measures on the epidemic in India, and explored strategies to exit lockdown. We obtained patient-level data to estimate the delay from onset to confirmation and the asymptomatic proportion. We estimated the basic and time-varying reproduction number (R0 and Rt) after adjusting for imported cases and delay to confirmation using incidence data from March 4 to April 25, 2020. Using a SEIR-QDPA model, we simulated lockdown relaxation scenarios and increased testing to evaluate lockdown exit strategies. R0 for India was estimated to be 2·08, and the Rt decreased from 1·67 on March 30 to 1·16 on April 22. We observed that the delay from the date of lockdown relaxation to the start of the second wave increases as lockdown is extended farther after the first wave peak-this delay is longer if lockdown is relaxed gradually. Aggressive measures such as lockdowns may be inherently enough to suppress an outbreak; however, other measures need to be scaled up as lockdowns are relaxed. Lower levels of social distancing when coupled with a testing ramp-up could achieve similar outbreak control as an aggressive social distancing regime where testing was not increased.
| S-EPMC7713576 | biostudies-literature
Project description:BackgroundAfter relaxing social distancing measures, South Korea experienced a resurgent second epidemic wave of coronavirus disease 2019 (COVID-19). In this study, we aimed to identify the transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and assess the impact of COVID-19 case finding and contact tracing in each epidemic wave.MethodsWe collected data on COVID-19 cases published by local public health authorities in South Korea and divided the study into two epidemic periods (19 January-19 April 2020 for the first epidemic wave and 20 April-11 August 2020 for the second epidemic wave). To identify changes in the transmissibility of SARS-CoV-2, the daily effective reproductive number (Rt) was estimated using the illness onset of the cases. Furthermore, to identify the characteristics of each epidemic wave, frequencies of cluster types were measured, and age-specific transmission probability matrices and serial intervals were estimated. The proportion of asymptomatic cases and cases with unknown sources of infection were also estimated to assess the changes of infections identified as cases in each wave.ResultsIn early May 2020, within 2-weeks of a relaxation in strict social distancing measures, Rt increased rapidly from 0.2 to 1.8 within a week and was around 1 until early July 2020. In both epidemic waves, the most frequent cluster types were religious-related activities and transmissions among the same age were more common. Furthermore, children were rarely infectors or infectees, and the mean serial intervals were similar (~ 3 days) in both waves. The proportion of asymptomatic cases at presentation increased from 22% (in the first wave) to 27% (in the second wave), while the cases with unknown sources of infection were similar in both waves (22 and 24%, respectively).ConclusionsOur study shows that relaxing social distancing measures was associated with increased SARS-CoV-2 transmission despite rigorous case findings in South Korea. Along with social distancing measures, the enhanced contact tracing including asymptomatic cases could be an efficient approach to control further epidemic waves.
| S-EPMC8154110 | biostudies-literature
Project description:BACKGROUND:On March 9, 2020, the first COVID-19 case was reported in Jodhpur, Rajasthan, in the northwestern part of India. Understanding the epidemiology of COVID-19 at a local level is becoming increasingly important to guide measures to control the pandemic. OBJECTIVE:The aim of this study was to estimate the serial interval and basic reproduction number (R0) to understand the transmission dynamics of the COVID-19 outbreak at a district level. We used standard mathematical modeling approaches to assess the utility of these factors in determining the effectiveness of COVID-19 responses and projecting the size of the epidemic. METHODS:Contact tracing of individuals infected with SARS-CoV-2 was performed to obtain the serial intervals. The median and 95th percentile values of the SARS-CoV-2 serial interval were obtained from the best fits with the weibull, log-normal, log-logistic, gamma, and generalized gamma distributions. Aggregate and instantaneous R0 values were derived with different methods using the EarlyR and EpiEstim packages in R software. RESULTS:The median and 95th percentile values of the serial interval were 5.23 days (95% CI 4.72-5.79) and 13.20 days (95% CI 10.90-18.18), respectively. R0 during the first 30 days of the outbreak was 1.62 (95% CI 1.07-2.17), which subsequently decreased to 1.15 (95% CI 1.09-1.21). The peak instantaneous R0 values obtained using a Poisson process developed by Jombert et al were 6.53 (95% CI 2.12-13.38) and 3.43 (95% CI 1.71-5.74) for sliding time windows of 7 and 14 days, respectively. The peak R0 values obtained using the method by Wallinga and Teunis were 2.96 (95% CI 2.52-3.36) and 2.92 (95% CI 2.65-3.22) for sliding time windows of 7 and 14 days, respectively. R0 values of 1.21 (95% CI 1.09-1.34) and 1.12 (95% CI 1.03-1.21) for the 7- and 14-day sliding time windows, respectively, were obtained on July 6, 2020, using method by Jombert et al. Using the method by Wallinga and Teunis, values of 0.32 (95% CI 0.27-0.36) and 0.61 (95% CI 0.58-0.63) were obtained for the 7- and 14-day sliding time windows, respectively. The projection of cases over the next month was 2131 (95% CI 1799-2462). Reductions of transmission by 25% and 50% corresponding to reasonable and aggressive control measures could lead to 58.7% and 84.0% reductions in epidemic size, respectively. CONCLUSIONS:The projected transmission reductions indicate that strengthening control measures could lead to proportionate reductions of the size of the COVID-19 epidemic. Time-dependent instantaneous R0 estimation based on the process by Jombart et al was found to be better suited for guiding COVID-19 response at the district level than overall R0 or instantaneous R0 estimation by the Wallinga and Teunis method. A data-driven approach at the local level is proposed to be useful in guiding public health strategy and surge capacity planning.
| S-EPMC7572116 | biostudies-literature
Project description:Since the first case reported of SARS-CoV-2 the end of December 2019 in China, the number of cases quickly climbed following an exponential growth trend, demonstrating that a global pandemic is possible. As of December 3, 2020, the total number of cases reported are around 65,527,000 contagions worldwide, and 1,524,000 deaths affecting 218 countries and territories. In this scenario, Spain is one of the countries that has suffered in a hard way, the ongoing epidemic caused by the novel coronavirus SARS-CoV-2, namely COVID-19 disease. In this paper, we present the utilization of phenomenological epidemic models to characterize the two first outbreak waves of COVID-19 in Spain. The study is driven using a two-step phenomenological epidemic approach. First, we use a simple generalized growth model to fit the main parameters at the early epidemic phase; later, we apply our previous finding over a logistic growth model to that characterize both waves completely. The results show that even in the absence of accurate data series, it is possible to characterize the curves of case incidence, and construct a short-term forecast of 60 days in the near time horizon, in relation to the expected total duration of the pandemic.
| S-EPMC8224976 | biostudies-literature
Project description:The causative organism, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical manifestations in disease-ridden patients. Differences in the severity of COVID-19 ranges from asymptomatic infections and mild cases to the severe form, leading to acute respiratory distress syndrome (ARDS) and multiorgan failure with poor survival. MiRNAs can regulate various cellular processes, including proliferation, apoptosis, and differentiation, by binding to the 3′UTR of target mRNAs inducing their degradation, thus serving a fundamental role in post-transcriptional repression. Alterations of miRNA levels in the blood have been described in multiple inflammatory and infectious diseases, including SARS-related coronaviruses. We used microarrays to delineate the miRNAs and snoRNAs signature in the peripheral blood of severe COVID-19 cases (n=9), as compared to mild (n=10) and asymptomatic (n=10) patients, and identified differentially expressed transcripts in severe versus asymptomatic, and others in severe versus mild COVID-19 cases. A cohort of 29 male age-matched patients were selected. All patients were previously diagnosed with COVID-19 using TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Waltham, Massachusetts), or Cobas SARS-CoV-2 Test (Roche Diagnostics, Rotkreuz, Switzerland), with a CT value < 30. Additional criterion for selection was age between 35 and 75 years. Participants were grouped into severe, mild and asymptomatic. Classifying severe cases was based on requirement of high-flow oxygen support and ICU admission (n=9). Whereas mild patients were identified based on symptoms and positive radiographic findings with pulmonary involvement (n=10). Patients with no clinical presentation were labelled as asymptomatic cases (n=10).
2022-03-01 | E-MTAB-10970 | biostudies-arrayexpress
Project description:The aim of the paper was to assess the differences in the mental distress of university students in the first and second waves of COVID-19, to compare these levels with that of the general population as well as to identify the risk factors associated with the changes in mental health. A total of 2,025 university students in core psychology courses in all years of study at the Faculty of Education at Palacký University Olomouc were approached via e-mail. Of this number of students, 800 students took part in the study, divided into two groups from the spring (N = 438) and autumn (N = 362) pandemic waves. The data were collected online via Google Forms using a battery of questionnaires and analyzed using the Wilcoxon-Mann-Whitney test, One-Sample Wilcoxon Signed Rank Test and binary logistic regression. The results showed a high prevalence of depressive symptoms (38.4 and 51.4%), significant anxiety (43.8 and 37%), and high stress (19.9 and 22.9%) among students in both waves of the pandemic. Depression and stress also increased significantly during the second wave compared with the first one (r = 0.18 [0.12, 0.25] and r = 0.08 [0.01, 0.14]). Finally, university students showed significantly higher levels of mental distress than the general population in all of the variables and in both waves (r = 0.42-0.86). A variety of factors influenced different aspects of mental distress in the spring and autumn pandemic waves. Emotion regulation emerged as the most significant and pervasive factor, both influencing all of the three indicators of mental distress and being a significant predictor in both waves.
| S-EPMC8729183 | biostudies-literature
Project description:Detection and isolation of infected people are believed to play an important role in the control of the COVID-19 pandemic. Some countries conduct large-scale screenings for testing, whereas others test mainly people with high prior probability of infection such as showing severe symptoms and/or having an epidemiological link with a known or suspected case or cluster of cases. However, what a good testing strategy is and whether the difference in testing strategy shows a meaningful, measurable impact on the COVID-19 epidemic remain unknown. Here, we showed that patterns of association between effective reproduction number (Rt) and test positivity rate can illuminate differences in testing situation among different areas, using global and local data from Japan. This association can also evaluate the adequacy of current testing systems and what information is captured in COVID-19 surveillance. The differences in testing systems alone cannot predict the results of epidemic containment efforts. Furthermore, monitoring test positivity rates and severe case proportions among the nonelderly can predict imminent case count increases. Monitoring test positivity rates in conjunction with the concurrent Rt could be useful to assess and strengthen public health management and testing systems and deepen understanding of COVID-19 epidemic dynamics.
| S-EPMC8125747 | biostudies-literature
Project description:BackgroundIn Ireland and across the European Union the COVID-19 epidemic waves, driven mainly by the emergence of new variants of the SARS-CoV-2 have continued their course, despite various interventions from governments. Public health interventions continue in their attempts to control the spread as they wait for the planned significant effect of vaccination.MethodsTo tackle this challenge and the observed non-stationary aspect of the epidemic we used a modified SEIR stochastic model with time-varying parameters, following Brownian process. This enabled us to reconstruct the temporal evolution of the transmission rate of COVID-19 with the non-specific hypothesis that it follows a basic stochastic process constrained by the available data. This model is coupled with Bayesian inference (particle Markov Chain Monte Carlo method) for parameter estimation and utilized mainly well-documented Irish hospital data.ResultsIn Ireland, mitigation measures provided a 78-86% reduction in transmission during the first wave between March and May 2020. For the second wave in October 2020, our reduction estimation was around 20% while it was 70% for the third wave in January 2021. This third wave was partly due to the UK variant appearing in Ireland. In June 2020 we estimated that sero-prevalence was 2.0% (95% CI: 1.2-3.5%) in complete accordance with a sero-prevalence survey. By the end of April 2021, the sero-prevalence was greater than 17% due in part to the vaccination campaign. Finally we demonstrate that the available observed confirmed cases are not reliable for analysis owing to the fact that their reporting rate has as expected greatly evolved.ConclusionWe provide the first estimations of the dynamics of the COVID-19 epidemic in Ireland and its key parameters. We also quantify the effects of mitigation measures on the virus transmission during and after mitigation for the three waves. Our results demonstrate that Ireland has significantly reduced transmission by employing mitigation measures, physical distancing and lockdown. This has to date avoided the saturation of healthcare infrastructures, flattened the epidemic curve and likely reduced mortality. However, as we await for a full roll out of a vaccination programme and as new variants potentially more transmissible and/or more infectious could continue to emerge and mitigation measures change silent transmission, challenges remain.
| S-EPMC8329614 | biostudies-literature