COVID-19 pandemic spread against countries' non-pharmaceutical interventions responses: a data-mining driven comparative study

Perspectives of stakeholders on barriers to COVID-19 protective behaviors adherence and vaccination among Myanmar migrant workers in southern Thailand: A qualitative study

Studies have been conducted on migrant health during the COVID-19 pandemic. However, in-depth information is scarce regarding the barriers to preventing COVID-19 in this vulnerable population. The objective of the study is to explore the barriers to COVID-19 protective behaviors adherence and vaccination among Myanmar migrant workers in Thailand. We conducted an interview-based qualitative study among 7 migrants from Myanmar, 6 Thai employers, and 9 Thai healthcare providers in the cities of Hat Yai and Pattani in Southern Thailand. We recruited participants by purposive sampling. We conducted in-depth interviews in-person or via telephone in Thai or Burmese language, transcribed the interview, and conducted thematic analysis. Regarding adherence to COVID-19 protective behaviors, two themes emerged: lifestyle and habit-related barriers, and non-vaccine supply chain management barriers. Regarding COVID-19 vaccination, three common themes emerged: fear, barriers related to health education and health promotion, and vaccine supply chain management. Supply chain management was a common theme in both domains. However, each domain also had additional themes. Our study contributed empirical findings that could be of interest to stakeholders in migrant health. However, limitations regarding the generalizability of the findings and social desirability should be considered in the interpretation of the findings.

Impact of non-pharmaceutical interventions on COVID-19 incidence and deaths: cross-national natural experiment in 32 European countries

PURPOSE

Non-pharmaceutical interventions (NPIs) have been the cornerstone of COVID-19 pandemic control, but evidence on their effectiveness varies according to the methods and approaches taken to empirical analysis. We analysed the impact of NPIs on incident SARS-CoV-2 across 32 European countries (March-December 2020) using two NPI trackers: the Corona Virus Pandemic Policy Monitor - COV-PPM, and the Oxford Covid-19 Government Response Tracker - OxCGRT.

METHODS

NPIs were summarized through principal component analysis into three sets, stratified by two waves (C1-C3, weeks 5-25, and C4-C6, weeks 35-52). Longitudinal, multi-level mixed-effects negative binomial regression models were fitted to estimate incidence rate ratios for cases and deaths considering different time-lags and reverse causation (i.e. changing incidence causing NPIs), stratified by waves and geographical regions (Western, Eastern, Northern, Southern, Others).

RESULTS

During the first wave, restrictions on movement/mobility, public transport, public events, and public spaces (C1) and healthcare system improvements, border closures and restrictions to public institutions (C2) were associated with a reduction in SARS-CoV-2 incidence after 28 and 35-days. Mask policies (C3) were associated with a reduction in SARS-CoV-2 incidence (except after 35-days). During wave 1, C1 and C2 were associated with a decrease in deaths after 49-days and C3 after 21, 28 and 35-days. During wave 2, restrictions on movement/mobility, public transport and healthcare system improvements (C5) were also associated with a decrease in SARS-CoV-2 cases and deaths across all countries.

CONCLUSION

In the absence of pre-existing immunity, vaccines or treatment options, our results suggest that the observed implementation of different categories of NPIs, showed varied associations with SARS-CoV-2 incidence and deaths across regions, and varied associations across waves. These relationships were consistent across components of NPIs derived from two policy trackers (CoV-PPM and OxCGRT).

Knowledge, attitudes, practices, and perception of COVID-19 preventive measures among adult residents of Matadi (Democratic Republic of the Congo) after the third epidemic wave

Background

Several governments from African countries, including the Democratic Republic of the Congo (DRC), implemented stringent public health measures to curb COVID-19 transmission in the early phases of the pandemic. While these restrictive measures are believed to have contributed to lowering case incidence and related mortality in DRC, data on the population's knowledge and adherence are limited. This study aimed to assess the knowledge, perception, attitudes, and practices of COVID-19 preventive measures and associated factors among adult residents of Matadi, thereby generating evidence for a strategy adjustment as the COVID-19 response is transitioning from emergency to control status.

Methods

We used data from a population-based cross-sectional study conducted in October 2021. Consenting participants were enrolled through a multi-stage cluster sampling approach and administered a pre-tested structured questionnaire using a mobile application (Epicollect 5). We analyzed adult participants' data using STATA 15.1. Univariable and multivariable analyses were applied to identify factors associated with good knowledge, good perception, positive attitude and good practice.

Results

We included 1,269 adult respondents for the secondary analysis. One respondent in six was female. The median age was 36 years (IQR 24-50). Most respondents (76.5%) had good knowledge. Respondents aged 40-49 years and those with vocational education level were 1.7 time (AOR 1.75, 95% CI 1.07-2.87) and twice as likely (AOR 2.06, 95% CI 1.01-4.21) to have good knowledge. Preventive measures were perceived as efficient by 45% of respondents. Good perception was associated with education level, profession, average household monthly income and good knowledge. Only 40% of respondents had a positive attitude. A positive attitude was associated with age, education level, and good knowledge. Respondents having good practice represented 5.8%. Good practice was associated with good knowledge, attitude and perception.

Conclusion

Most respondents were knowledgeable, had a good perception of government-related COVID-19 preventive measures, a moderately positive attitude and an extremely low level of good practice. Current COVID-19 preventive strategies, including vaccination rollout, need adjustment into high-efficiency, context-based and risk group-specific interventions. Evidence generated by this study will improve preparedness and response to future outbreaks.

Virological evidence of the impact of non-pharmaceutical interventions against COVID-19 in Ecuador, a resource-limited setting

Ecuador had substantial COVID-19-mortality during 2020 despite early implementation of non-pharmaceutical interventions (NPIs). Resource-limited settings like Ecuador have high proportions of informal labour which entail high human mobility, questioning efficacy of NPIs. We performed a retrospective observational study in Ecuador's national reference laboratory for viral respiratory infections during March 2020-February 2021 using stored respiratory specimens from 1950 patients, corresponding to 2.3% of all samples analysed within the Ecuadorian national surveillance system per week. During 2020, detection of SARS-CoV-2 (Pearson correlation; r = -0.74; p = 0.01) and other respiratory viruses (Pearson correlation; r = -0.68; p = 0.02) by real-time RT-PCR correlated negatively with NPIs stringency. Among respiratory viruses, adenoviruses (Fisher's exact-test; p = 0.026), parainfluenzaviruses (p = 0.04), enteroviruses (p < 0.0001) and metapneumoviruses (p < 0.0001) occurred significantly more frequently during months of absent or non-stringent NPIs (characterized by <55% stringency according to the Oxford stringency index data for Ecuador). Phylogenomic analyses of 632 newly characterized SARS-CoV-2 genomes revealed 100 near-parallel SARS-CoV-2 introductions during early 2020 in the absence of NPIs. NPI stringency correlated negatively with the number of circulating SARS-CoV-2 lineages during 2020 (r = -0.69; p = 0.02). Phylogeographic reconstructions showed differential SARS-CoV-2 dispersion patterns during 2020, with more short-distance transitions potentially associated with recreational activity during non-stringent NPIs. There were also fewer geographic transitions during strict NPIs (n = 450) than during non-stringent or absent NPIs (n = 580). Virological evidence supports that NPIs had an effect on virus spread and distribution in Ecuador, providing a template for future epidemics in resource-limited settings and contributing to a balanced assessment of societal costs entailed by strict NPIs.

Identification of an Optimal COVID-19 Booster Allocation Strategy to Minimize Hospital Bed-Days with a Fixed Healthcare Budget

Healthcare decision-makers face difficult decisions regarding COVID-19 booster selection given limited budgets and the need to maximize healthcare gain. A constrained optimization (CO) model was developed to identify booster allocation strategies that minimize bed-days by varying the proportion of the eligible population receiving different boosters, stratified by age, and given limited healthcare expenditure. Three booster options were included: B₁, costing US $1 per dose, B₂, costing US $2, and no booster (NB), costing US $0. B₁ and B₂ were assumed to be 55%/75% effective against mild/moderate COVID-19, respectively, and 90% effective against severe/critical COVID-19. Healthcare expenditure was limited to US$2.10 per person; the minimum expected expense using B_1, B_2, or NB for all. Brazil was the base-case country. The model demonstrated that B₁ for those aged <70 years and B₂ for those ≥70 years were optimal for minimizing bed-days. Compared with NB, bed-days were reduced by 75%, hospital admissions by 68%, and intensive care unit admissions by 90%. Total costs were reduced by 60% with medical resource use reduced by 81%. This illustrates that the CO model can be used by healthcare decision-makers to implement vaccine booster allocation strategies that provide the best healthcare outcomes in a broad range of contexts.

A machine learning algorithm to analyse the effects of vaccination on COVID-19 mortality

The coronavirus disease 2019 (COVID-19), with new variants, continues to be a constant pandemic threat that is generating socio-economic and health issues in manifold countries. The principal goal of this study is to develop a machine learning experiment to assess the effects of vaccination on the fatality rate of the COVID-19 pandemic. Data from 192 countries are analysed to explain the phenomena under study. This new algorithm selected two targets: the number of deaths and the fatality rate. Results suggest that, based on the respective vaccination plan, the turnout in the participation in the vaccination campaign, and the doses administered, countries under study suddenly have a reduction in the fatality rate of COVID-19 precisely at the point where the cut effect is generated in the neural network. This result is significant for the international scientific community. It would demonstrate the effective impact of the vaccination campaign on the fatality rate of COVID-19, whatever the country considered. In fact, once the vaccination has started (for vaccines that require a booster, we refer to at least the first dose), the antibody response of people seems to prevent the probability of death related to COVID-19. In short, at a certain point, the fatality rate collapses with increasing doses administered. All these results here can help decisions of policymakers to prepare optimal strategies, based on effective vaccination plans, to lessen the negative effects of the COVID-19 pandemic crisis in socioeconomic and health systems.

Impact of layered non-pharmacological interventions on COVID-19 transmission dynamics in Yucatan, Mexico

Background

The pandemic propagation of SARS-CoV-2 led to the adoption of a myriad of non-pharmacological interventions (NPIs, e.g., social distancing, mobility restrictions, gathering restrictions) in the Americas. Using national epidemiological data, here we report the impact of the layered adoption of multiple NPIs aimed at curving SARS-CoV-2 transmission in Yucatan State, Mexico.

Methods

Data from suspected and laboratory confirmed COVID-19 cases during 2020 were analyzed by age groups and sex, clinical signs, and symptoms as well as outcome. The impact of NPIs was quantified using time-varying reproduction numbers (R t) estimated as a time-series and by sectors of the city.

Findings

A total of 69,602 suspected cases were reported, 39.3% were laboratory-confirmed. Men were hospitalized (60.2%), more severely ill (3% vs 1.9%) and more likely to die (62%) than women. Early in the outbreak, all sectors in Merida hadR t estimates above unity. Once all NPÍs were in place,R t values were dramatically reduced below one, and in the last interval transmission estimates ofR t remained below one in all sectors.

Interpretation

In the absence of a COVID-19 vaccination program, the combination and wide adherence of NPÍs led to a low and stable trend in SARS-CoV-2 transmission that did not overwhelm the health sector. Our study reflects that a controlled and planned ease of restrictions to balance health, social and economic recovery resulted in a single wave of transmission that prolonged at low and stable levels.

Funding

GVP received funding from Emory University via the MP3 Initiative.

The COVID-19 pandemic in the African continent

In December 2019, a new coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and associated disease, coronavirus disease 2019 (COVID-19), was identified in China. This virus spread quickly and in March, 2020, it was declared a pandemic. Scientists predicted the worst scenario to occur in Africa since it was the least developed of the continents in terms of human development index, lagged behind others in achievement of the United Nations sustainable development goals (SDGs), has inadequate resources for provision of social services, and has many fragile states. In addition, there were relatively few research reporting findings on COVID-19 in Africa. On the contrary, the more developed countries reported higher disease incidences and mortality rates. However, for Africa, the earlier predictions and modelling into COVID-19 incidence and mortality did not fit into the reality. Therefore, the main objective of this forum is to bring together infectious diseases and public health experts to give an overview of COVID-19 in Africa and share their thoughts and opinions on why Africa behaved the way it did. Furthermore, the experts highlight what needs to be done to support Africa to consolidate the status quo and overcome the negative effects of COVID-19 so as to accelerate attainment of the SDGs.

The Impact of COVID-19 on Mortality in Italy: Retrospective Analysis of Epidemiological Trends

BACKGROUND

Despite the available evidence on its severity, COVID-19 has often been compared with seasonal flu by some conspirators and even scientists. Various public discussions arose about the noncausal correlation between COVID-19 and the observed deaths during the pandemic period in Italy.

OBJECTIVE

This paper aimed to search for endogenous reasons for the mortality increase recorded in Italy during 2020 to test this controversial hypothesis. Furthermore, we provide a framework for epidemiological analyses of time series.

METHODS

We analyzed deaths by age, sex, region, and cause of death in Italy from 2011 to 2019. Ordinary least squares (OLS) linear regression analyses and autoregressive integrated moving average (ARIMA) were used to predict the best value for 2020. A Grubbs 1-sided test was used to assess the significance of the difference between predicted and observed 2020 deaths/mortality. Finally, a 1-sample t test was used to compare the population of regional excess deaths to a null mean. The relationship between mortality and predictive variables was assessed using OLS multiple regression models. Since there is no uniform opinion on multicomparison adjustment and false negatives imply great epidemiological risk, the less-conservative Siegel approach and more-conservative Holm-Bonferroni approach were employed. By doing so, we provided the reader with the means to carry out an independent analysis.

RESULTS

Both ARIMA and OLS linear regression models predicted the number of deaths in Italy during 2020 to be between 640,000 and 660,000 (range of 95% CIs: 620,000-695,000) against the observed value of above 750,000. We found strong evidence supporting that the death increase in all regions (average excess=12.2%) was not due to chance (t21=7.2; adjusted P<.001). Male and female national mortality excesses were 18.4% (P<.001; adjusted P=.006) and 14.1% (P=.005; adjusted P=.12), respectively. However, we found limited significance when comparing male and female mortality residuals' using the Mann-Whitney U test (P=.27; adjusted P=.99). Finally, mortality was strongly and positively correlated with latitude (R=0.82; adjusted P<.001). In this regard, the significance of the mortality increases during 2020 varied greatly from region to region. Lombardy recorded the highest mortality increase (38% for men, adjusted P<.001; 31% for women, P<.001; adjusted P=.006).

CONCLUSIONS

Our findings support the absence of historical endogenous reasons capable of justifying the mortality increase observed in Italy during 2020. Together with the current knowledge on SARS-CoV-2, these results provide decisive evidence on the devastating impact of COVID-19. We suggest that this research be leveraged by government, health, and information authorities to furnish proof against conspiracy hypotheses that minimize COVID-19-related risks. Finally, given the marked concordance between ARIMA and OLS regression, we suggest that these models be exploited for public health surveillance. Specifically, meaningful information can be deduced by comparing predicted and observed epidemiological trends.

Use of COVID-19 Test Positivity Rate, Epidemiological, and Clinical Tools for Guiding Targeted Public Health Interventions

India experienced a second wave of COVID-19 infection with an unprecedented upsurge in the number of cases. We have analyzed the effect of different restrictive measures implemented in six Indian states. Further, based on available national and international data on disease transmission and clinical presentation, we have proposed a decision-making matrix for planning adequate resources to combat the future waves of COVID-19. We conclude that pragmatic and well calibrated localized restrictions, tailored as per specific needs may achieve a decline in disease transmission comparable to drastic steps like national lockdowns. Additionally, we have underscored the critical need for countries to generate local epidemiological, clinical and laboratory data alongwith community perception and uptake of various non-pharmaceutical interventions, for effective planning and policy making.

The impact of declaring the state of emergency on human mobility during COVID-19 pandemic in Japan

Background/objectives

Japan has responded to the spread of COVID-19 through declaration of a state of emergency to regulate human mobility. Although the declaration was enforced by the government for prefectures, there is limited evidence as to whether the public complied with requests for voluntary stay at home. In this study, we evaluated the impact of declaring a state of emergency on human mobility during the COVID-19 pandemic in Japan.

Methods

We utilized daily human mobility data for 47 prefectures in Japan. Data were collected via mobile phone from February 1, 2020 to April 30, 2021. Difference-in-difference analysis was utilized to estimate the effects of the declaration of a state of emergency on prefectures in the Tokyo Metropolitan Area (Tokyo, Kanagawa, Saitama, and Chiba) in comparison to other prefectures where the state of emergency was first lifted (Osaka, Hyogo, Fukuoka, and Aichi).

Results

Human mobility was suppressed during the second state of emergency, from January 8 to March 21, 2021. However, the impact was weaker for the second state of emergency compared to the first.

Conclusion

In Japan, government requests for stay at home, such as the declaration of a state of emergency, were temporarily able to control human mobility. However, the second state of emergency was not as effective as the first. If additional need to regulate human mobility arises, self-restraint with stronger enforcement should be considered.

Responses against infectious disease pandemics: a narrative review on COVID-19

Currently, the world is facing the coronavirus disease 2019 (COVID-19) pandemic. With this, an emerging infectious disease pandemic in the absence of effective antiviral agents and vaccines for a novel virus is no different from the 1918 influenza pandemic, which became a great disaster for humankind. We also experienced a global lockdown with a stringent implementation of social distancing, which is a first for mankind living in the present day, and has led to enormous economic damage and restrictions on individual freedom. The microorganism that will cause the next pandemic may be a highly fatal avian influenza virus, another coronavirus, or a completely different microorganism. This COVID-19 pandemic is an enormous lesson for humankind and is tantamount to a vaccine in preparation for the next pandemic. Important and urgent undertakings were given to each country in terms of complementing laws and regulations for a stronger and more resilient healthcare system, such as investment in research and development for new rapid diagnostic technologies, vaccines, new therapeutic agents, among others.