What is the required quantity of COVID-19 vaccines for outbreak prevention? A global analysis based on growth curve modeling (preprint)

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.

Evaluation of risk factors associated with SARS-CoV-2 transmission.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused high morbidity and mortality worldwide. Since there is not enough evidence of risk factors of SARS-CoV-2 transmission, this study aimed to evaluate them. METHODS: This survey-based study was conducted across 66 countries from May to November 2020 among suspected and confirmed individuals with COVID-19. The stepwise AIC method was utilized to determine the optimal multivariable logistic regression to explore predictive factors of SARS-CoV-2 transmission. RESULTS: Among 2372 respondents who participated in the study, there were 1172 valid responses. The profession of non-healthcare-worker (OR: 1.77, 95%CI: 1.04-3.00, p = .032), history of SARS-CoV or MERS-CoV infection (OR: 4.78, 95%CI: 2.34-9.63, p < .001), higher frequency of contact with colleagues (OR: 1.17, 95%CI: 1.01-1.37, p = .041), and habit of hugging when greeting (OR: 1.25, 95%CI: 1.00-1.56, p = .049) were associated with an increased risk of contracting COVID-19. Current smokers had a lower likelihood of having COVID-19 compared to former smokers (OR: 5.41, 95%CI: 1.93-17.49, p = .002) or non-smokers (OR: 3.69, 95%CI: 1.48-11.11, p = .01). CONCLUSIONS: Our study suggests several risk factors for SARS-CoV-2 transmission including the profession of non-healthcare workers, history of other coronavirus infections, frequent close contact with colleagues, the habit of hugging when greeting, and smoking status.

Since there is not enough evidence of risk factors of SARS-CoV-2 transmission, this study aimed to evaluate them. The risk of SARS-CoV-2 infection was higher among non-healthcare workers and among those who had a history of being tested positive for SARS-CoV or MERS-CoV before the COVID-19 outbreak. The habit of frequent contact with colleagues or hugging when greeting significantly increased the risk of being infected with SARS-CoV-2. The current smokers had a lower risk of getting infected with SARS-CoV-2 than others who had a habit of smoking tobacco in the past or who had never smoked.

Predicting Anxiety and Depression Among Patients With COVID-19 in Concentrated Isolation at Medical Camps in Vietnam: A Descriptive Cross-Sectional Study.

Introduction: This study aims to assess the requirement for anxiety and depression treatment for patients with coronavirus disease 2019 (COVID-19) in medical camps in Bac Giang province, Vietnam. This information can help improve the government policy to reduce anxiety and depression in patients with COVID-19. Methods: A total of patients with 427 COVID-19 participated in the survey conducted from 5 to 15 June 2021 in Bac Giang province. The survey included 17 questions about the general characteristics of the patients, 15 questions to assess common COVID-19 symptoms, the Patient Health Questionnaire-9 (PHQ-9), and General Anxiety Disorder-7 (GAD-7) scores, and four questions to assess hospital reviews, including facilities, food, medical staff, and living conditions. Logistics regression analyses were conducted to assess the association between COVID-19 symptoms and high anxiety and depression (HAD) status. Results: A logistic regression analysis evaluated the risk factors in need of intervention. Our study showed that lower hospital review scores (odd ratio = 0.98; 95% confident interval = 0.97-0.99) were found to be a risk needing intervention. It was also identified that older patients (odd ratio = 1.1; 95% confident interval = 1.03-1.18), women (odd ratio = 1.31; 95% confident interval = 1.09-1.31), patients who were primary income earners in the family (odd ratio = 1.15; 95% confident interval = 1.03-1.28), patients who had headaches (odd ratio = 1.16; 95% confident interval = 1.06-1.21), and patients who had joint pain (odd ratio = 1.17; 95% confident interval = 1.06- 1.3) were risk factors for HAD status. Conclusion: Our research shows that every 10-year age increase was associated with a 10% increase in the likelihood of HAD status. Study subjects being primary income earners were also associated with a 15% increased risk of having HAD status. This study showed that a decrease in family income due to COVID-19 caused an increase in high-level anxiety/depression status.

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type.

Early centralized isolation strategy for all confirmed cases of COVID-19 remains a core intervention to disrupt the pandemic spreading significantly.

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.