Linking key intervention timings to rapid declining effective reproduction number to quantify lessons against COVID-19

Risk perceptions and behaviors concerning rural tourism and economic-political drivers of COVID-19 policy in 2020

When COVID-19 was first introduced to the United States, state and local governments enacted a variety of policies intended to mitigate the virulence of the epidemic. At the time, the most effective measures to prevent the spread of COVID-19 included stay-at-home orders, closing of nonessential businesses, and mask mandates. Although it was well known that regions with high population density and cold climates were at the highest risk for disease spread, rural counties that are economically reliant on tourism were incentivized to enact fewer precautions against COVID-19. The uncertainty of the COVID-19 pandemic, the multiple policies to reduce transmission, and the changes in outdoor recreation behavior had a significant impact on rural tourism destinations and management of protected spaces. We utilize fine-scale incidence and demographic data to study the relationship between local economic and political concerns, COVID-19 mitigation measures, and the subsequent severity of outbreaks throughout the continental United States. We also present results from an online survey that measured travel behavior, health risk perceptions, knowledge and experience with COVID-19, and evaluation of destination attributes by 407 out-of-state visitors who traveled to Maine from 2020 to 2021. We synthesize this research to present a narrative on how perceptions of COVID-19 risk and public perceptions of rural tourism put certain communities at greater risk of illness throughout 2020. This research could inform future rural destination management and public health policies to help reduce negative socioeconomic, health and environmental impacts of pandemic-derived changes in travel and outdoor recreation behavior.

Relationship between social inequality perception patterns and depressive symptoms among Chinese adults: A national representative longitudinal study

BACKGROUND

The rising prevalence of depressive symptoms presents a pressing global public health concern, exacerbated by prevailing social inequality.

AIM

This study seeks to identify latent profiles of social inequality perception and explore their associations with depressive symptoms.

METHODS

Data were obtained from the China Family Panel Studies (CFPS) involving 10,529 residents aged 18 years and above. Latent profile analysis (LPA) was used to identify different patterns of social inequality perception. Multiple linear regression analysis examined the links between these patterns and depressive symptoms.

RESULTS

Three distinct patterns of social inequality perception were identified: the disappointed pattern (TDP), the neutral pattern (TNP), and the positive pattern (TPP). Perceived social inequality was significantly associated with short-term and long-term depressive symptoms (β = .51, 95% CI [0.29, 0.72] vs. β = .51, 95% CI [0.27, 0.74]). Increases in social inequality perception patterns were also related to more severe depressive symptoms (β = .55, 95% CI [0.36, 0.74]).

CONCLUSIONS

Increasing perceived social inequality is closely linked to elevated depressive symptoms in Chinese adults. This underscores the need for tailored strategies aimed at addressing heightened perceptions of social inequality to reduce the risk of depressive symptoms.

A Strategy Formulation Framework for Efficient Screening during the Early Stage of a Pandemic

For viruses that can be transmitted by contacts of people, efficiently screening infected individuals is beneficial for controlling outbreaks rapidly and avoiding widespread diffusion, especially during the early stage of a pandemic. The process of virus transmission can be described as virus diffusion in complex networks such as trajectory networks. We propose a strategy formulation framework (SFF) for generating various screening strategies to identify influential nodes in networks. We propose two types of metrics to measure the nodes' influence and three types of screening modes. Then, we can obtain six combinations, i.e., six strategies. To verify the efficiencies of the strategies, we build a scenario model based on the multi-agent modelling. In this model, people can move according to their self-decisions, and a virtual trajectory network is generated by their contacts. We found that (1) screening people will have a better performance based on their contact paths if there is no confirmed case yet, and (2) if the first confirmed case has been discovered, it is better to screen people sequentially by their influences. The proposed SFF and strategies can provide support for decision makers, and the proposed scenario model can be applied to simulate and forecast the virus-diffusion process.

Effectiveness of non-pharmaceutical public health interventions against COVID-19: A systematic review and meta-analysis

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people's life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population's other health problems than COVID-19.

Where is the Third E in Controlling Coronavirus Disease-19 in Indonesia? A Mini Review

Coronavirus disease (COVID-19) continues to attract global attention and is the most serious health problem today. Indonesia faces a very significant spike in cases in mid-2021. This may be related to inadequate enforcement before cases reach their peak. To review what has happened and what should be done in the future, this paper presents the three Es concept to be applied more consistently in efforts to control COVID-19 in Indonesia.

Modeling and staged assessments of the controllability of spread for repeated outbreaks of COVID-19

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been causing an outbreak of a new type of pneumonia globally, and repeated outbreaks have already appeared. Among the studies on the spread of the COVID-19, few studies have investigated the repeated outbreaks in stages, and the quantitative condition of a controllable spread has not been revealed. In this paper, a brief compartmental model is developed. The effective reproduction number (ERN) of the model is interpreted by the ratio of net newly infectious individuals to net isolation infections to assess the controllability of the spread of COVID-19. It is found that the value of the ERN at the inflection point of the pandemic is equal to one. The effectiveness of the quarantine, even the treatment, is parametrized in various stages with Gompertz functions to increase modeling accuracy. The impacts of the vaccinations are discussed by adding a vaccinated compartment. The results show that the sufficient vaccinations can make the inflection point appear early and significantly reduce subsequent increases in newly confirmed cases. The analysis of the ERNs of COVID-19 in the United States, Spain, France, and Peru confirms that the condition of a repeated outbreak is to relax or lift the interventions related to isolation and quarantine interventions to a level where the ERN is greater than one.

An AHP-based regional COVID-19 vulnerability model and its application in China

Since the COVID-19 outbreak, four cities-Wuhan, Beijing, Urumqi and Dalian-have experienced the process from outbreak to stabilization. According to the China Statistical Yearbook and China Center for Disease Control records, regional, pathological, medical and response attributes were selected as regional vulnerability factors of infectious diseases. Then the Analytic Hierarchy Process (AHP) method was used to build a regional vulnerability index model for the infectious disease. The influence of the COVID-19 outbreak at a certain place was assessed computationally in terms of the number of days of epidemic duration and cumulative number of infections, and then fitted to the city data. The resulting correlation coefficient was 0.999952. The range of the regional vulnerability index for COVID-19 virus was from 0.0513 to 0.9379. The vulnerability indexes of Wuhan, Urumqi, Beijing and Dalian were 0.8733, 0.1951, 0.1566 and 0.1119, respectively. The lack of understanding of the virus became the biggest breakthrough point for the rapid spread of the virus in Wuhan. Due to inadequate prevention and control measures, the city of Urumqi was unable to trace the source of infection and close contacts, resulting in a relatively large impact. Beijing has both high population density and migration rate, which imply that the disease outbreak in this city had a great impact. Dalian has perfect prevention and good regional attributes. In addition, the regional vulnerability index model was used to analyze other Chinese cities. Accordingly, the regional vulnerability index and the prevention and control suggestions for them were discussed.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40808-021-01244-y.

Streamlining the dental care during COVID-19 pandemic: updated clinical recommendations and infection control management framework

Several guidelines for dental practice have been published by dental associations and regulatory boards since the beginning of the pandemic. Initially, all non-emergency dental treatment were suspended. Healthcare personnel around the world are gradually expanding back to elective procedures. International updated recommendations alert that professionals must maintain regular observation of local health department reports, ensure personal protective equipment, and screen all patients for COVID-19 signs and symptoms. Telehealth strategies, patient screening, rescheduling when presenting COVID-19 symptoms and/or history of contact with infected people and hand/environment hygiene practices are reinforced. Appropriate cleaning and surface disinfection are mandatory. The dental staff must be trained to use appropriate Personal Protective Equipment (PPE), following a risk assessment and standard precautions: gloves; fluid resistant disposable gown, eye protection (face shield or goggles) and a medical mask. A fit tested N95 or KN95 respirator (or higher) is recommended when aerosol generating procedures are performed. Only essential accompanying persons should attend to dental appointment with the patient and must wear a cloth face covering or facemask. Social distancing and mask wearing by all staff are necessary in all areas of the office. Dental health care providers should keep up to date to the current guidance of clinical practice during the pandemic.

Current understanding of the influence of environmental factors on SARS-CoV-2 transmission, persistence, and infectivity

Coronavirus disease 2019 (COVID-19) has emerged as a significant public health emergency in recent times. It is a respiratory illness caused by the novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was initially reported in late December 2019. In a span of 6 months, this pandemic spread across the globe leading to high morbidity and mortality rates. Soon after the identification of the causative virus, questions concerning the impact of environmental factors on the dissemination and transmission of the virus, its persistence in environmental matrices, and infectivity potential begin to emerge. As the environmental factors could have far-reaching consequences on infection dissemination and severity, it is essential to understand the linkage between these factors and the COVID-19 outbreak. In order to improve our current understanding over this topic, the present article summarizes topical and substantial observations made regarding the influences of abiotic environmental factors such as climate, temperature, humidity, wind speed, air, and water quality, solid surfaces/interfaces, frozen food, and biotic factors like age, sex, gender, blood type, population density, behavioural characteristics, etc. on the transmission, persistence, and infectivity of this newly recognized SARS-CoV-2 virus. Further, the potential pathways of virus transmission that could pose risk to population health have been discussed, and the critical areas have been identified which merits urgent research for the assessment and management of the COVID-19 outbreak. Where possible, the knowledge gaps requiring further investigation have been highlighted.

Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location

The purpose of this study is to investigate whether the relationship between meteorological factors (i.e., daily maximum temperature, minimum temperature, average temperature, temperature range, relative humidity, average wind speed and total precipitation) and COVID-19 transmission is affected by season and geographical location during the period of community-based pandemic prevention and control. COVID-19 infected case records and meteorological data in four cities (Wuhan, Beijing, Urumqi and Dalian) in China were collected. Then, the best-fitting model of COVID-19 infected cases was selected from four statistic models (Gaussian, logistic, lognormal distribution and allometric models), and the relationship between meteorological factors and COVID-19 infected cases was analyzed using multiple stepwise regression and Pearson correlation. The results showed that the lognormal distribution model was well adapted to describing the change of COVID-19 infected cases compared with other models (R2 > 0.78; p-values < 0.001). Under the condition of implementing community-based pandemic prevention and control, relationship between COVID-19 infected cases and meteorological factors differed among the four cities. Temperature and relative humidity were mainly the driving factors on COVID-19 transmission, but their relations obviously varied with season and geographical location. In summer, the increase in relative humidity and the decrease in maximum temperature facilitate COVID-19 transmission in arid inland cities, while at this point the decrease in relative humidity is good for the spread of COVID-19 in coastal cities. For the humid cities, the reduction of relative humidity and the lowest temperature in the winter promote COVID-19 transmission.

Past, present, and future of COVID-19: a review

SARS-CoV-2 has recently emerged, becoming a global threat, affecting directly all human beings owing to its morbidity and mortality and indirectly, due to the enormous economic and psychological impact produced by social isolation, the most effective measure so far, but unsustainable for a long period. The scientific effort to understand and control SARS-CoV-2 transmission and clinical impact has been huge, and important achievements are highlighted in this review. Diagnosis is central and is the first step in recognizing and fighting any infectious agent. Instrumental to that is the quality of the data, relying on serological and molecular surveys in addition to trustworthy clinical records. However, the fast spread of a virus adapted for human-to-human respiratory transmission raised a demand for millions of molecular tests that are simply not available. Several candidate drugs are under evaluation in clinical trials. Those with an already recognized safety profile are more auspicious, since, if proven effective, can cut several steps of production and phase 2 and 3 trials. More than one hundred vaccine prototypes are in different stages of development, however, safety and efficacy evaluations cannot be obviated, implicating, most optimistically, in at least months for us to have an effective immunization, the definite measure to allow a safe return to the pre-pandemic lifestyle. Science has never been more necessary and present in daily life. Relying on the best of human wit is the only way out to this pandemic, saving as many lives as possible.