Effects of public health interventions on the epidemiological spread during the first wave of the COVID-19 outbreak in Thailand.
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ABSTRACT:
SUBMITTER: Triukose S
PROVIDER: S-EPMC7894963 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Effects of public health interventions on the epidemiological spread during the first wave of the COVID-19 outbreak in Thailand.
Triukose Sipat S Nitinawarat Sirin S Satian Ponlapat P Somboonsavatdee Anupap A Chotikarn Ponlachart P Thammasanya Thunchanok T Wanlapakorn Nasamon N Sudhinaraset Natthinee N Boonyamalik Pitakpol P Kakhong Bancha B Poovorawan Yong Y
PloS one 20210219 2
A novel infectious respiratory disease was recognized in Wuhan (Hubei Province, China) in December 2019. In February 2020, the disease was named "coronavirus disease 2019" (COVID-19). COVID-19 became a pandemic in March 2020, and, since then, different countries have implemented a broad spectrum of policies. Thailand is considered to be among the top countries in handling its first wave of the outbreak-12 January to 31 July 2020. Here, we illustrate how Thailand tackled the COVID-19 outbreak, pa ...[more]
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Project description:Background: A key challenge in estimating epidemiological parameters for a pandemic such as the initial COVID-19 outbreak in Wuhan is the discrepancy between the officially reported number of infections and the true number of infections. A common approach to tackling the challenge is to use the number of infections exported from the originating city to infer the true number. This approach can only provide a static estimate of the epidemiological parameters before city lockdown because there are almost no exported cases thereafter. Methods: We propose a Bayesian estimation method that dynamically estimates the epidemiological parameters by recovering true numbers of infections from day-to-day official numbers. To illustrate the use of this method, we provide a comprehensive retrospection on how the COVID-19 had progressed in Wuhan from January 19 to March 5, 2020. Particularly, we estimate that the outbreak sizes by January 23 and March 5 were 11,239 [95% CI 4,794–22,372] and 124,506 [95% CI 69,526–265,113], respectively. Results: The effective reproduction number attained its maximum on January 24 (3.42 [95% CI 3.34–3.50]) and became less than 1 from February 7 (0.76 [95% CI 0.65–0.92]). We also estimate the effects of two major government interventions on the spread of COVID-19 in Wuhan. Conclusions: This case study by our proposed method affirms the believed importance and effectiveness of imposing tight nonessential travel restrictions and affirm the importance and effectiveness of government interventions (e.g., transportation suspension and large scale hospitalization) for effective mitigation of COVID-19 community spread. Significance for public health In fighting global pandemic such as COVID-19, an important early task for understanding the spread is to closely monitor the infection size and assess the disease epidemiological parameters. The in- sights gained from the epidemiological parameter estimation enable public health practitioners to dynamically monitor the temporal spread trend and to quantitatively analyze the effectiveness of new public health policies. In this paper, we aim to address a key technical challenge potentially arising from the under-reporting issues in pandemic early periods, and critically re-examine the COVID-19 situation at the initial epicenter Wuhan city as a practically relevant case study. Methodological development for modeling dynamic evolution involving parameter estimation therefore has important public health applications and is expected to have significant impact on modeling practice for understanding future epidemic events well beyond COVID-19.
| S-EPMC7967497 | biostudies-literature
Project description:The government of India implemented social distancing interventions to contain the COVID-19 epidemic. However, effects of these interventions on epidemic dynamics are yet to be understood. Rates of laboratory-confirmed COVID-19 infections per day and effective reproduction number (Rt ) were estimated for 7 periods (Pre-lockdown, Lockdown Phases 1 to 4 and Unlock 1-2) according to nationally implemented interventions with phased relaxation. Adoption of these interventions was estimated using Google mobility data. Estimates at the national level and for 12 Indian states most affected by COVID-19 are presented. Daily case rates ranged from 0.03 to 285.60/10 million people across 7 discrete periods in India. From 18 May to 31 July 2020, the NCT of Delhi had the highest case rate (999/10 million people/day), whereas Madhya Pradesh had the lowest (49/10 million/day). Average Rt was 1.99 (95% CI 1.93-2.06) and 1.39 (95% CI 1.38-1.40) for the entirety of India during the period from 22 March 2020 to 17 May 2020 and from 18 May 2020 to 31 July 2020, respectively. Median mobility in India decreased in all contact domains during the period from 22 March 2020 to 17 May 2020, with the lowest being 21% in retail/recreation, except home which increased to 129% compared to the 100% baseline value. Median mobility in the 'Grocery and Pharmacy' returned to levels observed before 22 March 2020 in Unlock 1 and 2, and the enhanced mobility in the Pharmacy sector needs to be investigated. The Indian government imposed strict contact mitigation, followed by a phased relaxation, which slowed the spread of COVID-19 epidemic progression in India. The identified daily COVID-19 case rates and Rt will aid national and state governments in formulating ongoing COVID-19 containment plans. Furthermore, these findings may inform COVID-19 public health policy in developing countries with similar settings to India.
| S-EPMC7675717 | biostudies-literature
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| S-EPMC8782428 | biostudies-literature
Project description:ImportanceCoronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak.ObjectiveTo evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions.Design, setting, and participantsIn this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients' age, sex, residential location, occupation, and severity classification.ExposuresNonpharmaceutical public health interventions including cordons sanitaire, traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey.Main outcomes and measuresRates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 (cordons sanitaire, traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods.ResultsAmong 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (≥80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI, 3.31-3.95]) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1.Conclusions and relevanceA series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions.
| S-EPMC7149375 | biostudies-literature
Project description:BackgroundThe novel coronavirus disease 2019 (COVID-19) pandemic has spread from China to the rest of the world. Africa seems less impacted with lower number of cases and deaths than other continents. Senegal recorded its first case on March 2, 2020. We present here data collected from March 2 to October 31, 2020 in Senegal.MethodsSocio-demographic, epidemiological, clinical and virological information were collected on suspected cases. To determine factors associated with diagnosed infection, symptomatic disease and death, multivariable binary logistic regression and log binomial models were used. Epidemiological parameters such as the reproduction number and growth rate were estimated.Results67,608 suspected cases were tested by the IPD laboratories (13,031 positive and 54,577 negative). All age categories were associated with SARS-CoV-2 infection, but also patients having diabetes or hypertension or other cardiovascular diseases. With diagnosed infection, patients over 65 years and those with hypertension and cardiovascular disease and diabetes were highly associated with death. Patients with co-morbidities were associated with symptomatic disease, but only the under 15 years were not associated with. Among infected, 27.67% were asymptomatic (40.9% when contacts were systematically tested; 12.11% when only symptomatic or high-risk contacts were tested). Less than 15 years-old were mostly asymptomatic (63.2%). Dakar accounted for 81.4% of confirmed cases. The estimated mean serial interval was 5.57 (± 5.14) days. The average reproduction number was estimated at 1.161 (95%CI: 1.159-1.162), the growth rate was 0.031 (95%CI: 0.028-0.034) per day.ConclusionsOur findings indicated that factors associated with symptomatic COVID-19 and death are advanced age (over 65 years-old) and comorbidities such as diabetes and hypertension and cardiovascular disease.
| S-EPMC9488827 | biostudies-literature
Project description:BackgroundTo control the spread of coronavirus disease 2019 (COVID-19), governments are increasingly relying on the public to voluntarily manage risk. Effectiveness is likely to rely in part on how much the public trusts the Government's response. We examined the English public's trust in the Conservative Government to control the spread of COVID-19 after the initial 'crisis' period.MethodsWe analyzed eight rounds of a longitudinal survey of 1899 smartphone users aged 18-79 in England between October 2020 and December 2021. We fitted a random-effects logit model to identify personal characteristics and opinions associated with trust in the Conservative Government to control the spread of COVID-19.ResultsTrust was lowest in January 2021 (28%) and highest in March 2021 (44%). Being older, having lower educational attainment and aligning with the Conservative Party were predictors of higher levels of trust. Conversely, being less deprived, reporting that Government communications were not clear and considering that the measures taken by the Government went too far or not far enough were predictors of being less likely to report a great deal or a fair amount of trust in the Government to control the pandemic.ConclusionTrust in the Government's response was found to be low throughout the study. Our findings suggest that there may be scope to avoid losing trust by aligning Government actions more closely with scientific advice and public opinion, and through clearer public health messaging. However, it remains unclear whether and how higher trust in the Government's response would increase compliance with Government advice.
| S-EPMC10710334 | biostudies-literature
Project description:ObjectiveIn order to reduce distress associated with working with COVID-19 patients, several psychological intervention programmes for healthcare workers have been developed in Spain. We aimed to describe the main characteristics and components of these programmes for healthcare workers treating COVID-19 patients in Spanish hospitals.Material and methodsAn online survey was designed to evaluate the main characteristics of psychological intervention programmes for healthcare workers during the first wave of COVID-19 pandemic.ResultsValid responses were received from 36 hospitals. Most of these programmes offered both in-person and online therapy. The most common aim of these interventions was emotional regulation, which was treated by psychoeducational and cognitive-behavioural techniques in individual interventions. Group interventions mainly used psychoeducation and mindfulness. Only half of the teams that offered in-person interventions received training in the proper use of personal protective equipment.ConclusionsSeveral hospitals in Spain have developed mental health interventions for healthcare workers during the COVID-19 pandemic, deploying a wide range of therapeutic modalities and techniques. The rapid implementation of these programmes during the pandemic suggests that safety may not have received sufficient attention. The planning and development of interventions for healthcare workers during pandemics merits greater attention by national and regional authorities and institutions.
| S-EPMC8194007 | biostudies-literature
Project description:ObjectiveIn order to reduce distress associated with working with COVID-19 patients, several psychological intervention programmes for healthcare workers have been developed in Spain. We aimed to describe the main characteristics and components of these programmes for healthcare workers treating COVID-19 patients in Spanish hospitals.Material and methodsAn online survey was designed to evaluate the main characteristics of psychological intervention programmes for healthcare workers during the first wave of COVID-19 pandemic.ResultsValid responses were received from 36 hospitals. Most of these programmes offered both in-person and online therapy. The most common aim of these interventions was emotional regulation, which was treated by psychoeducational and cognitive-behavioural techniques in individual interventions. Group interventions mainly used psychoeducation and mindfulness. Only half of the teams that offered in-person interventions received training in the proper use of personal protective equipment.ConclusionsSeveral hospitals in Spain have developed mental health interventions for healthcare workers during the COVID-19 pandemic, deploying a wide range of therapeutic modalities and techniques. The rapid implementation of these programmes during the pandemic suggests that safety may not have received sufficient attention. The planning and development of interventions for healthcare workers during pandemics merits greater attention by national and regional authorities and institutions.
| S-EPMC7859719 | biostudies-literature
Project description:BackgroundPrevious studies have highlighted the increased risk of contracting the COVID-19 for health-care workers and suggest that oral health-care workers may carry the greatest risk. Considering the transmission route of the SARS-CoV-2 infection, a similar increased risk can be hypothesized for other respiratory infections. However, no study has specifically assessed the risk of contracting COVID-19 within the dental profession.MethodsAn online survey was conducted within a population of French dental professionals between April 1 and April 29, 2020. Univariable and multivariable logistic regression analyses were performed to explore risk indicators associated with laboratory-confirmed COVID-19 and COVID-19-related clinical phenotypes (i.e. phenotypes present in 15% or more of SARS-CoV-2-positive cases).Results4172 dentists and 1868 dental assistants responded to the survey, representing approximately 10% of French oral health-care workers. The prevalence of laboratory-confirmed COVID-19 was 1.9% for dentists and 0.8% for dental assistants. Higher prevalence was found for COVID-19-related clinical phenotypes both in dentists (15.0%) and dental assistants (11.8%). Chronic kidney disease and obesity were associated with increased odds of laboratory-confirmed COVID-19, whereas working in a practice limited to endodontics was associated with decreased odds. Chronic obstructive pulmonary disease, use of public transportation and having a practice limited to periodontology were associated with increased odds of presenting a COVID-19-related clinical phenotype. Moreover, changes in work rhythm or clinical practice were associated with decreased odds of both outcomes.ConclusionsAlthough oral health-care professionals were surprisingly not at higher risk of COVID-19 than the general population, specific risk indicators could exist, notably among high aerosol-generating dental subspecialties such as periodontology. Considering the similarities between COVID-19-related clinical phenotypes other viral respiratory infections, lessons can be learned from the COVID-19 pandemic regarding the usefulness of equipping and protecting oral health-care workers, notably during seasonal viral outbreaks, to limit infection spread.ImpactResults from this study may provide important insights for relevant health authorities regarding the overall infection status of oral health-care workers in the current pandemic and draw attention to particular at-risk groups, as illustrated in the present study. Protecting oral health-care workers could be an interesting public health strategy to prevent the resurgence of COVID-19 and/or the emergence of new pandemics.
| S-EPMC7877573 | biostudies-literature
Project description:When the unprecedented COVID-19 pandemic first spread, governments could implement a wide range of measures to tackle the outbreaks. Conventional wisdom holds that public health policy should be made on the basis of empirical demonstrations, while little research has probed on how to safeguard the expected policy utility in the case of evidence shortage on novel contagious diseases. In particular, the fight against COVID-19 cannot succeed without public compliance as well as the support of people who have not tested positive. Based on the data from the first wave of COVID-19, by using a random effect estimator, fixed effect method, and hierarchical technique, we specified the efficiency of particular social distancing policies by contextualizing multiple factors. We found that adopting gathering restrictions decreased new case growth but were conditional on its interaction with population density, while mitigation effects constantly corresponded to policy magnitude in a given time; for which the effective patterns varied from three days to sixty days. Overall, policies encouraging social distancing exerted a positive effect on mitigating the first wave of COVID-19. Both the enforcing duration and public compliance constrained the expected impact of nonpharmaceutical intervention according to degrees of policy level. These findings suggest that, when evidence is incomplete, the effectiveness of public health crisis management depends on the combination of policy appropriateness and, accordingly, public compliance.
| S-EPMC8997917 | biostudies-literature