Spatiotemporal distribution of COVID-19 during the first 7 months of the epidemic in Vietnam
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ABSTRACT:
SUBMITTER: Manabe T
PROVIDER: S-EPMC8556820 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundInternational air travel plays an important role in the global spread of SARS-CoV-2, and tracing of close contacts is an integral part of the public health response to COVID-19. We aimed to assess the timeliness of contact tracing among airline passengers arriving in Vietnam on flights containing COVID-19 cases and investigated factors associated with timeliness of contact tracing.MethodsWe included data from 2228 passengers on 22 incoming flights between 2 and 19 March 2020. Contact tracing duration was assessed separately for the time between the date of index case confirmation and date of contact tracing initiation (interval I), and the date of contact tracing initiation and completion (interval II). We used log-rank tests and multivariable Poisson regression models to identify factors associated with timeliness.ResultsThe median duration of interval I and interval II was one (IQR: 1-2) and 3 days (IQR: 2-5), respectively. The contact tracing duration was shorter for passengers from flights where the index case was identified through mandatory testing directly upon arrival (median = 4; IQR: 3-5) compared to flights with index case detection through self-presentation at health facilities after arrival (median = 7; IQR: 5-8) (p-value = 0.018). Cumulative hazards for successful tracing were higher for Vietnamese nationals compared to non-Vietnamese nationals (p < 0.001).ConclusionsContact tracing among flight passengers in the early stage of the COVID-19 epidemic in Vietnam was timely though delays occurred on high workload days. Mandatory SARS-CoV-2 testing at arrival may reduce contact tracing duration and should be considered as an integrated screening tool for flight passengers from high-risk areas when entering low-transmission settings with limited contact tracing capacity. We recommend a standardized risk-based contact tracing approach for flight passengers during the ongoing COVID-19 epidemic.
| S-EPMC8080478 | biostudies-literature
Project description:BackgroundUnderstanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data.MethodsWe conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs.ResultsThe corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16-23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms.ConclusionsInformation collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.
| S-EPMC9130991 | biostudies-literature
Project description:BackgroundA range of near-real-time online/mobile mapping dashboards and applications have been used to track the coronavirus disease 2019 (COVID-19) pandemic worldwide; however, small area-based spatiotemporal patterns of COVID-19 in the United States remain unknown.MethodsWe obtained county-based counts of COVID-19 cases confirmed in the United States from 22 January to 13 May 2020 (N = 1 386 050). We characterized the dynamics of the COVID-19 epidemic through detecting weekly hotspots of newly confirmed cases using Spatial and Space-Time Scan Statistics and quantifying the trends of incidence of COVID-19 by county characteristics using the Joinpoint analysis.ResultsAlong with the national plateau reached in early April, COVID-19 incidence significantly decreased in the Northeast (estimated weekly percentage change [EWPC]: -16.6%) but continued increasing in the Midwest, South, and West (EWPCs: 13.2%, 5.6%, and 5.7%, respectively). Higher risks of clustering and incidence of COVID-19 were consistently observed in metropolitan versus rural counties, counties closest to core airports, the most populous counties, and counties with the highest proportion of racial/ethnic minorities. However, geographic differences in incidence have shrunk since early April, driven by a significant decrease in the incidence in these counties (EWPC range: -2.0%, -4.2%) and a consistent increase in other areas (EWPC range: 1.5-20.3%).ConclusionsTo substantially decrease the nationwide incidence of COVID-19, strict social-distancing measures should be continuously implemented, especially in geographic areas with increasing risks, including rural areas. Spatiotemporal characteristics and trends of COVID-19 should be considered in decision making on the timeline of re-opening for states and localities.
| S-EPMC7454424 | biostudies-literature
Project description:As the COVID-19 outbreak traveled through various Italian regions, all national and local administrations issued measures to counter the spread of the contagion and organize healthcare. The Italian healthcare system is, indeed, a decentralized system with 21 regional health systems (RHSs), with different models of healthcare service delivery and organization. This study investigates whether a different organization of RHSs would have led to different management of the COVID-19 epidemic, and evaluates the effect of different approaches in epidemic management on the COVID-19 epidemiological trend. A set of indicators is identified by conducting an online synchronous Focus Group, involving an experts panel. A Pearson's correlation test was performed on the values assumed by the historical series of indicators investigate correlations among the trends represented by the indicators or between them and external factors. The comparison between the experiences of the different Italian regions, regarding the management of the epidemic, has helped to confirm and emphasize the importance of a community-based approach in health care-integrated with the hospital's functions for the care of complex conditions and the need for specialized assistance.
| S-EPMC8125969 | biostudies-literature
Project description:Social distancing in response to the COVID-19 pandemic brought several modifications in our daily lives. With these changes, some people have reported alterations in their feelings of how fast time was passing. In this study, we assessed whether and how social distancing and the evolution of the COVID-19 pandemic influenced participants' time awareness and production of time intervals. Participants (n = 3855) filled in the first questionnaire approximately 60 days after the start of social distancing in Brazil and weekly questionnaires for 15 weeks during social distancing. Our results indicate that time was perceived as expanded at the beginning, but this feeling decreased across the weeks. Time awareness was strongly associated with psychological factors such as loneliness, stress, and positive emotions, but not with time production. This relation was shown between participants and within their longitudinal reports. Together, our findings show how emotions are a crucial aspect of how time is felt.
| S-EPMC9007501 | biostudies-literature
Project description:ObjectivesThe novel coronavirus (COVID-19) epidemic is reaching its final phase in China. The epidemic data are available for a complete assessment of epidemiological parameters in all regions and time periods.MethodsThis study aims to present a spatiotemporal epidemic model based on spatially stratified heterogeneity (SSH) to simulate the epidemic spread. A susceptible-exposed/latent-infected-removed (SEIR) model was constructed for each SSH-identified stratum (each administrative city) to estimate the spatiotemporal epidemiological parameters of the outbreak.ResultsWe estimated that the mean latent and removed periods were 5.40 and 2.13 days, respectively. There was an average of 1.72 latent or infected persons per 10,000 Wuhan travelers to other locations until January 20th, 2020. The space-time basic reproduction number (R0) estimates indicate an initial value between 2 and 3.5 in most cities on this date. The mean period for R0 estimates to decrease to 80%, and 50% of initial values in cities were an average of 14.73 and 19.62 days, respectively.ConclusionsOur model estimates the complete spatiotemporal epidemiological characteristics of the outbreak in a space-time domain. These findings will help enhance a comprehensive understanding of the outbreak and inform the strategies of prevention and control in other countries worldwide.
| S-EPMC8056483 | biostudies-literature
Project description:In recent history, Coronavirus Disease 2019 (COVID-19) is one of the worst infectious disease outbreaks affecting humanity. The World Health Organization has defined the outbreak of COVID-19 as a pandemic, and the massive growth of the number of infected cases in a short time has caused enormous pressure on medical systems. Mexico surpassed 3.7 million confirmed infections and 285,000 deaths on October 23, 2021. We analysed the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We computed weekly Moran's I index to assess spatial autocorrelation over time and identify clusters of the disease using the "flexibly shaped spatial scan" approach. Finally, we compared Euclidean, cost, resistance distances and gravitational model to select the best-suited approach to predict inter-municipality contagion. We found that COVID-19 pandemic in Mexico is characterised by clusters evolving in space and time as parallel epidemics. The gravitational distance was the best model to predict newly infected municipalities though the predictive power was relatively low and varied over time. This study helps us understand the spread of the epidemic over the Mexican territory and gives insights to model and predict the epidemic behaviour.
| S-EPMC8711283 | biostudies-literature
Project description:ImportanceThe COVID-19 pandemic disrupted the normal course of cancer screening and detection in the US. A nationwide analysis of the extent of this disruption using cancer registry data has not been conducted.ObjectiveTo assess the observed and expected cancer rate trends for March through December 2020 using data from all 50 US states and the District of Columbia.Design, settings, and participantsThis was a population-based cross-sectional analysis of cancer incidence trends using data on cases of invasive cancer diagnosis reported to the US Cancer Statistics from January 1, 2018, through December 31, 2020. Data analyses were performed from July 6 to 28, 2023.Exposure(s)Age, sex, race, urbanicity, and state-level response to the COVID-19 pandemic at the time of cancer diagnosis.Main outcomes and measuresUsed time-series forecasting methods to calculate expected cancer incidence rates for March 1 through December 31, 2020, from prepandemic trends (January 2018-February 2020). Measured relative difference between observed and expected cancer incidence rates and numbers of potentially missed cancer cases.ResultsThis study included 1 297 874 cancer cases reported in the US from March 1 through December 31, 2020, with an age-adjusted incidence rate of 326.5 cases per 100 000 population. Of the observed cases, 657 743 (50.7%) occurred in male patients, 757 106 (58.3%) in persons 65 years or older, and 1 066 566 (82.2%) in White individuals. Observed rates of all-sites cancer incidence in the US were 28.6% (95% prediction interval [PI], 25.4%-31.7%) lower than expected during the height of the COVID-19 pandemic response (March-May 2020); 6.3% (95% PI, 3.8%-8.8%) lower in June to December 2020; and overall, 13.0% (95% PI, 11.2%-14.9%) lower during the first 10 months of the pandemic. These differences indicate that there were potentially 134 395 (95% PI, 112 544-156 680) undiagnosed cancers during that time frame. Prostate cancer accounted for the largest number of potentially missed cases (22 950), followed by female breast (16 870) and lung (16 333) cancers. Screenable cancers saw a total rate reduction of 13.9% (95% PI, 12.2%-15.6%) compared with the expected rate. The rate of female breast cancer showed evidence of recovery to previous trends after the first 3 months of the pandemic, but levels remained low for colorectal, cervical, and lung cancers. From March to May 2020, states with more restrictive COVID-19 responses had significantly greater disruptions, yet by December 2020, these differences were nonsignificant for all sites except lung, kidney, and pancreatic cancer.Conclusions and relevanceThis cross-sectional analysis of cancer incidence trends found a substantial disruption to cancer diagnoses in the US during the first 10 months of the COVID-19 pandemic. The overall and differential findings can be used to inform where the US health care system should be looking to make up ground in cancer screening and detection.
| S-EPMC10884945 | biostudies-literature
Project description:BackgroundFew robust longitudinal data on long-term coronavirus disease 2019 (COVID-19) symptoms are available. We evaluated symptom onset, severity and recovery across the full spectrum of disease severity, up to one year after illness onset.MethodsThe RECoVERED Study is a prospective cohort study based in Amsterdam, the Netherlands. Participants aged ≥18 years were enrolled following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis via the local public health service and from hospitals. Standardized symptom questionnaires were completed at enrollment, 1 week and month later, and monthly thereafter. Clinical severity was defined according to World Health Organization (WHO) criteria. Kaplan-Meier methods were used to compare time from illness onset to symptom recovery, by clinical severity. We examined determinants of time to recovery using multivariable Cox proportional hazards models.ResultsBetween 11 May 2020 and 1 May 2021, 342 COVID-19 patients (192 [56%] male) were enrolled, of whom 99/342 (29%) had mild, 145/342 (42%) moderate, 56/342 (16%) severe, and 42/342 (12%) critical disease. The proportion of participants who reported at least 1 persistent symptom at 12 weeks after illness onset was greater in those with severe/critical disease (86.7% [95% confidence interval {CI} = 76.5-92.7%]) compared to those with mild or moderate disease (30.7% [95% CI = 21.1-40.9%] and 63.8% [95% CI = 54.8-71.5%], respectively). At 12 months after illness onset, two-fifths of participants (40.7% [95% CI = 34.2-7.1]) continued to report ≥1 symptom. Recovery was slower in female compared to male participants (adjusted hazard ratio [aHR] 0.65 [95% CI = .47-.92]) and those with a body mass index [BMI] ≥30kg/m2 compared to BMI <25kg/m2 (hazard ratio [HR] 0.62 [95% CI = .39-.97]).ConclusionsCOVID-19 symptoms persisted for one year after illness onset, even in some individuals with mild disease. Female sex and obesity were the most important determinants of speed of recovery from symptoms.
| S-EPMC8522402 | biostudies-literature
Project description:BackgroundThe first nationwide lockdown due to the COVID-19 pandemic was implemented in Vietnam from April 1 to 15, 2020. Nevertheless, there has been limited information on the impact of COVID-19 on the psychological health of the public.ObjectiveThis study aimed to estimate the prevalence of psychological issues and identify the factors associated with the psychological impact of COVID-19 during the first nationwide lockdown among the general population in Vietnam.MethodsWe employed a cross-sectional study design with convenience sampling. A self-administered, online survey was used to collect data and assess psychological distress, depression, anxiety, and stress of participants from April 10 to 15, 2020. The Impact of Event Scale-Revised (IES-R) and the Depression, Anxiety, and Stress Scale-21 (DASS-21) were utilized to assess psychological distress, depression, anxiety, and stress of participants during social distancing due to COVID-19. Associations across factors were explored using regression analysis.ResultsA total of 1385 respondents completed the survey. Of this, 35.9% (n=497) experienced psychological distress, as well as depression (n=325, 23.5%), anxiety (n=195, 14.1%), and stress (n=309, 22.3%). Respondents who evaluated their physical health as average had a higher IES-R score (beta coefficient [B]=9.16, 95% CI 6.43 to 11.89), as well as higher depression (B=5.85, 95% CI 4.49 to 7.21), anxiety (B=3.64, 95% CI 2.64 to 4.63), and stress (B=5.19, 95% CI 3.83 to 6.56) scores for DASS-21 than those who rated their health as good or very good. Those who self-reported their health as bad or very bad experienced more severe depression (B=9.57, 95% CI 4.54 to 14.59), anxiety (B=7.24, 95% CI 3.55 to 10.9), and stress (B=10.60, 95% CI 5.56 to 15.65). Unemployment was more likely to be associated with depression (B=3.34, 95% CI 1.68 to 5.01) and stress (B=2.34, 95% CI 0.84 to 3.85). Regarding worries about COVID-19, more than half (n=755, 54.5%) expressed concern for their children aged <18 years, which increased their IES-R score (B=7.81, 95% CI 4.98 to 10.64) and DASS-21 stress score (B=1.75, 95% CI 0.27 to 3.24). The majority of respondents (n=1335, 96.4%) were confident about their doctor's expertise in terms of COVID-19 diagnosis and treatment, which was positively associated with less distress caused by the outbreak (B=-7.84, 95% CI -14.58 to -1.11).ConclusionsThe findings highlight the effect of COVID-19 on mental health during the nationwide lockdown among the general population in Vietnam. The study provides useful evidence for policy decision makers to develop and implement interventions to mitigate these impacts.
| S-EPMC7935248 | biostudies-literature