Background In response to the spread of the coronavirus disease 2019 (COVID-19), plenty of control measures were proposed. To assess the impact of current control measures on the number of new case indices 14 countries with the highest confirmed cases, highest mortality rate, and having a close relationship with the outbreak’s origin; were selected and analyzed. Methods In the study, we analyzed the impact of five control measures, including centralized isolation of all confirmed cases, closure of schools, closure of public areas, closure of cities, and closure of borders of the 14 targeted countries according to their timing; by comparing its absolute effect average, its absolute effect cumulative, and its relative effect average. Results Our analysis determined that early centralized isolation of all confirmed cases was represented as a core intervention in significantly disrupting the pandemic’s spread. This strategy helped in successfully controlling the early stage of the outbreak when the total number of cases were under 100, without the requirement of the closure of cities and public areas, which would impose a negative impact on the society and its economy. However, when the number of cases increased with the apparition of new clusters, coordination between centralized isolation and non-pharmaceutical interventions facilitated control of the crisis efficiently. Conclusion Early centralized isolation of all confirmed cases should be implemented at the time of the first detected infectious case.

BackgroundVietnam was one of the countries pursuing the goal of “Zero-COVID” and had effectively achieved it in the first three waves of the pandemic. However, the spread of the Delta variant was outbreak first in Vietnam in late April 2021, in which Ho Chi Minh City was the worst affected. This study surveyed the public's knowledge, attitude, perception, and practice (KAPP) toward COVID-19 during the rapid rise course of the outbreak in Ho Chi Minh City.MethodsThis cross-sectional survey was conducted from 30th September to 16th November 2021, involving 963 residents across the city. We asked residents a series of 21 questions. The response rate was 76.6%. We set a priori level of significance at α = 0.05 for all statistical tests.ResultsThe residents' KAPP scores were 68.67% ± 17.16, 77.33% ± 18.71, 74.7% ± 26.25, and 72.31% ± 31, respectively. KAPP scores of the medical staff were higher than the non-medical group. Our study showed positive, medium–strong Pearson correlations between knowledge and practice (r = 0.337), attitude and practice (r = 0.405), and perception and practice (r = 0.671; p < 0.05). We found 16 rules to estimate the conditional probabilities among KAPP scores via the association rule mining method. Mainly, 94% confident probability of participants had {Knowledge=Good, Attitude=Good, Perception=Good}, as well as {Practice=Good} (in rule 9 with support of 17.6%). In opposition to around 86% to 90% of the times, participants had levels of {Perception=Fair, Practice=Poor} given with either {Attitude=Fair} or {Knowledge=Fair} (according to rules 1, 2, and rules 15, 16 with a support of 7–8%).ConclusionIn addition to the government's directives and policies, citizens' knowledge, attitude, perception, and practice are considered one of the critical preventive measures during the COVID-19 pandemic. The results affirmed the good internal relationship among K, A, P, and P scores creating a hierarchy of healthcare educational goals and health behavior among residents.

Introduction The SARS-CoV-2 virus, which has the ability to rapidly spread, has caused multiple waves of deaths, resulting in nearly 7 million deaths in the past 3 years. During the early phase, most governments focused on implementing strict measures to cut off the transmission vector. However, the introduction of COVID-19 vaccines has changed the course of the fight against the COVID-19 pandemic. Methods A joinpoint regression analysis was used to identify mortality waves in 224 countries from February 22nd, 2020, to March 1st, 2023. Only countries with at least 2 waves were included in the analysis using Superimposition by Translation And Rotation (SITAR) to determine the growth curve of daily deaths and the impact of COVID-19 vaccine doses per population (CVDP), Cumulative incidence of COVID-19 (CIC), Rate of active cases per hospital bed (RAPHB), Active cases with diabetes (ACD), and Stringency index (SI). Results The analysis included over 3 million COVID-19 deaths from 82 countries to construct the growth curve. The increase in CVDP was associated with a decrease in wave size, intensity, and duration. However, an increase in CIC, ACD, RAHB, and SI was related to an increase in wave intensity and duration. The results suggest that maintaining CVDP at 120% (equivalent to 60% full doses) was associated with a decrease of 94.4% in COVID-19 deaths. Conclusion This research offers evidence for governments to enhance COVID-19 vaccination efforts in order to maintain herd immunity at 60% of the population and consider avoiding strict control measures.

Background: The SARS-CoV-2 pandemic has cost millions of deaths and lifelong consequences since December 2019. We attempted to evaluate the incidence, distribution, and risk factors associated with death after applying the social distance strategy to the second wave of SARS-CoV-2 in the Danang outbreak (July 2020), Vietnam. Methods: We retrospectively reviewed the online Danang Hospital reports, gathering the epidemiological history of confirmed SARS-CoV-2 patients. We then conducted a descriptive analysis of Fisher's Phi Coefficient and Cramer's, along with multiple logistic regression models to test the effects of symptomatology and control measures performed by the Vietnamese government on transmission dynamics. The last report we examined was on August 29, 2020.Results: 389 SARS-CoV-2 confirmed cases related to the Danang outbreak are included in our analysis with a mean age of 47.1 (SD = 18.4), involving 154 men and 235 women, 34 cases of death, and 355 were alive. The study showed significant results related to age, quarantine measures, previous negative SARS-CoV-2 test, and a range of symptoms, including shortness of breath and myalgia (p-value < 0.05). Our multiple-variable analysis suggested the significant risk of death was related to age, severe symptomology, undetected SARS-CoV-2 test results, and prior quarantined SARS-CoV-2 history.Conclusions: Vietnamese authorities had implemented successful quarantine practices to control the SARS-CoV-2 outbreaks. However, this virus has shown dynamic spread beyond the ability of the country to control its transmission. Adequate screening, social distancing, and adequate care of the elderly and healthcare workers can lower the risk of future outbreaks.

Background: The Japanese government advised mild or asymptomatic coronavirus disease-2019 (COVID-19) cases to self-isolate at home, while more severe individuals were treated at health posts. Poor compliance with self-isolation could be a potential reason for the new outbreak. Our study aimed to find out the correlation between the rising new cases of COVID-19 and home-based patients in Japan. Methods: A secondary data analysis study was conducted with the data from COVID-19- involved databases collected from Johns Hopkins University, Japanese Ministry of Health, Labour and Welfare, and Community Mobility Reports of Google. New community cases, stringency index, number of tests, and active cases were analyzed. Using a linear regression model, an independent variable was utilized for a given date to predict the future number of community cases. Results: Research results show that outpatient cases, the stringency, and Google Mobility Trend were all significantly associated with the number of COVID-19 community cases from the sixth day to the ninth day. The model predicting community cases on the eighth day (R2=0.8906) was the most appropriate showing outpatients, residential index, grocery and pharmacy index, retail and recreation index, and workplaces index were positively related (β1=24.2, 95% CI: 20.3– 26.3, P<0.0001; β2=277.7, 95% CI: 171.8–408.2, P<0.0001; β3=112.4, 95% CI: 79.8–158.3, P<0.0001; β4=73.1, 95% CI: 53- 04.4, P<0.0001; β5=57.2, 95% CI: 25.2–96.8, P=0.001, respectively). In contrast, inpatients, park index, and adjusted stringency index were negatively related to the number of community cases (β6=-2.8, 95% CI: -3.9 – -1.6, P<0.0001; β7=-33, 95% CI: -43.6 – -27, P<0.0001; β8=-14.4, 95% CI: -20.1– -12, P<0.0001, respectively). Conclusion: Outpatient cases and indexes of Community Mobility Reports were associated with COVID-19 community cases.