ABSTRACT
Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessening the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Method(s): To investigate whether inactivated vaccines were effective in protecting against COVID-19 infections, we estimated the odds ratio (OR) of the vaccination in COVID-19 cases vs. matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied the multivariate stepwise Logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Result(s): Out of the 153,544 COVID-19 patients included in the analysis, 118,124 (76.9%) patients had been vaccinated and 143,225(93.3%) were asymptomatic patients. Of the 10,319 symptomatic patients, 10,031(97.2%), 281(2.7%) and 7(0.1%) experienced mild, moderate, and severe infections, respectively. There is no evidence that the vaccination helped protect from infections (OR=0.82, p=0.613). The vaccination, however, offered a small but significant protection against symptomatic infections (RR=0.92, p < 0.001) and halved the risk of moderate/severe infections (OR=0.48, 95% CI: 0.37 - 0.61). Older age (> 60 years) and malignant tumors were significantly associated with moderate/severe infections. Gender also appeared to be a risk factor for symptomatic infections, with females being associated with a lower risk for moderate/severe illness. Conclusion(s): Inactivated COVID-19 vaccines helped provide a small but significant protection against symptomatic infections and halved risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking COVID-19 Omicron variant community spread.Copyright © 2023
ABSTRACT
Background: The COVID-19 pandemic catalyzed innovation in infection control measures, including widespread deployment of digital contact tracing systems. However, these technologies were not well understood by the general public and were complex for the public health community to implement, hampering adoption. Objective(s): To provide an overview of existing digital contact tracing systems, creating a framework for understanding design elements that impact their effectiveness as public health tools and offering a rubric for decision-makers to evaluate different systems for selection and implementation. Method(s): Scientific literature and publicly available information from relevant health authorities and other stakeholders was reviewed. Information was synthesized to develop a conceptual framework explaining how key design elements impact effectiveness of digital contact tracing systems and highlighting opportunities for future improvement. Result(s): A range of digital contact tracing interventions were deployed by governments worldwide and several professional sports leagues. Key design elements of the systems include: (1) data architecture (i.e., centralized versus decentralized systems, impacting privacy guarantees and data availability);(2) proximity detection technology (e.g., type of device signaling);(3) alert logic and timing (e.g., time- and distance-based criteria affecting sensitivity and specificity of alerts;real-time proximity alerts and/or bidirectional contact tracing, determining scope of infection prevention);(4) population (eligibility and availability);and (5) the structural and public health context of intervention (e.g., availability and timeliness of testing). Several systems demonstrated effectiveness in preventing transmission during COVID-19, though numerous limitations have also been documented in the literature. Conclusion(s): Digital contact tracing systems have the potential to mitigate the economic and public health impact of future infectious disease outbreaks, reducing community transmission and detecting potential cases earlier in the disease course. Lessons learned from solutions deployed during the COVID-19 pandemic provide an opportunity to improve multiple aspects of these systems, enhancing preparedness for future outbreaks.Copyright © 2023
ABSTRACT
The outbreak of COVID-19 caused human activities to be affected in one way or another. As a result, measures were put in place by various national governments to reduce the spread of the virus. This paper examines adherence to COVID-19 guidelines in Nigeria among itinerant traders, using a total of 40 eligible participants from selected local governments in Enugu state, Nigeria. The study adapted purposive sampling techniques to identify eligible participants;while in-depth interview was the method used for data collection. Among other findings, result shows that the control measures rolled out by government were seriously undermined. Nomadic traders, driven by economic gains, played covert role in the spread of the virus. This signalled a weak link in the efforts to curb the spread of the virus in Nigeria. The study contributes to a more exact diagnosis of the weak link in the efforts to contain the spread of the virus and how the quest for economic gains drove the abuse of COVID-19 mitigation protocols with its attendant health implications. It therefore recommends that government should strengthen the institutional capacity for detection and control, and provide the critical infrastructural facilities that will make for intensified surveillance in future epidemic or pandemic outbreak. Economic incentives and the effective monitoring of protocol enforcers saddled with the responsibility of enforcing government directives are also encouraged in order to curb compromise. © 2023, Fudan University.
ABSTRACT
Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81:1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers' markets, medical workers and other key areas and groups, and ensure early detection and timely response.Copyright © 2022 China Tropical Medicine. All rights reserved.
ABSTRACT
There are many unknowns surrounding COVID-19 and the ongoing pandemic. Standard epidemiological methods helped to determine the initial and ongoing distribution of COVID-19 in time and space, with unprecedented global coverage in almost real-time, and the forecasting methods used already had a reasonable predictive ability. Cumulative incidence and other complex epidemiological estimators have been widely disseminated via the media and are becoming lay terms thanks to persistent use, but their thresholds to determine public health interventions are yet to achieve consensus. The natural history of SARS-CoV-2, the interplay of risk factors and the effectiveness of mitigating factors in subpopulations remain unmet challenges. Establishing standard definitions of COVID-19 and its consequences is essential to the implementation of research. Pending widespread vaccine coverage, the world is experiencing unleashed community transmission in many countries, and the COVID-19 endgame is a distant goal. Several characteristics differentiate the transmissibility of SARS-CoV-2 from other viruses, making COVID-19 much more difficult to control with universal hygiene interventions. Epidemiology remains a necessary discipline to help end the COVID-19 pandemic;economic, social and health policy decision-making analysis are also needed.Copyright © ERS 2021.
ABSTRACT
Background: As COVID-19 cases persist, one potential intervention to reduce absenteeism in the workplace due to COVID-19 is to use rapid antigen diagnostics to mitigate the spread of SARS-CoV-2. Furthermore, routine testing in the workplace offers an avenue to reaching a large proportion of the population which could lead to a greater community impact beyond solely mitigating transmission events that occur in the workplace. We sought to identify the most cost-effective workplace testing strategies at the community level and within individual workplaces. Method(s): We used two models to understand how SARS-CoV-2 AgRDTs could best be implemented within the workplace to mitigate the spread of COVID-19. In our community-level dynamic transmission model, PATAT, we evaluated the impact of symptomatic testing and asymptomatic testing of a fixed proportion of the formally employed workforce on broader community transmission. We stratified runs by asymptomatic testing frequency, vaccine coverage, vaccine effectiveness, and Rt. Simulations were informed using demographic data from Georgia, Brazil, and the Netherlands. We conducted a cost-effectiveness analysis using the results from each country and assumed a $2.50 total cost per test. Result(s): We observed a substantial decrease in the number of infections occurring in both the workplace and community when a SARS-CoV-2 AgRDTs strategy was implemented. Under all conditions, mandatory symptomatic testing and related quarantine from the workplace averted up to 72%, 79%, and 74% of community infections in Brazil, Georgia, and the Netherlands respectively. Limiting tests to symptomatic workers was always on the cost-effectiveness frontier, regardless of the vaccine coverage, efficacy, or Rt of the virus (Figure 1), at $2-$4 per workplace infection prevented. While asymptomatic testing was on the cost-effectiveness frontier, it would cost an additional $500-$6700 to prevent one additional workplace infection. The added benefit of routine asymptomatic testing was minimal until 100% of the workforce was reached. Conclusion(s): We found self-testing with AgRDTs for the formally employed workforce is both efficient at reducing workplace and community infections as well as cost-effective when targeting symptomatic individuals. Willingness to pay to avoid workplace absenteeism may differ by country, individual workplaces, and the perceived economic value of several workdays missed. If there is a higher willingness to pay, routine asymptomatic screening may be considered.
ABSTRACT
Real-world effectiveness studies are important for monitoring the performance of COVID-19 vaccination strategies and informing COVID-19 prevention and control policies. The Real-World Effectiveness of COVID-19 Vaccine under the Malaysian National COVID-19 Immunisation Program (RECoVaM) analysed effectiveness of a range of homologous primary, as well as heterologous and homologous booster COVID-19 vaccines, which comprised of BNT162b2 (mRNA), CoronaVac (inactivated) and AZD1222 (viral vectored), against SARS-CoV-2 infection and severe COVID-19. Nationally comprehensive administrative data at both individual- and aggregate-levels were consolidated for each analysis. These were the Malaysia national COVID-19 vaccinations register (MyVAS), COVID-19 cases line listing, intensive care unit (ICU) admissions register, deaths line listing, supervised test registry (SIMKA), and the MySejahtera check-ins-based automated contact tracing registry (AutoTrace). RECoVaM adopted several observational study designs. Exposure periods were carefully calibrated to account for the structure of Malaysia's COVID-19 data, and epidemiological context, to estimate vaccine effectiveness. Importantly, RECoVaM also compared effectiveness measures during both the Delta-dominant, and Omicron-dominant periods. Effectiveness estimates for primary vaccinations showed a reduction in risk of SARS-CoV-2 infections by 87 - 91%, and symptomatic infections by 85 - 89%, as well as ICU admission by 82 - 84% among COVID-19 cases, and death by 86 - 88% among COVID-19 cases. All vaccine platforms were effective in reducing risk against ICU admission and death. Subsequently, significant waning of protection was demonstrated against COVID-19 infection among BNT162b2 (90.8 to 79.3%) and CoronaVac (74.5 to 30.4%) recipients 3 to 5 months post-primary vaccinations. Protection against ICU admission for CoronaVac waned (56.0 to 28.7%) and was more substantial among the elderly (aged 60 years and above). The estimates of marginal Vaccine Effectiveness (mVE) for boosters showed that recipients of booster doses were at least 90% less likely to be infected with COVID-19 relative to primary BNT162b2 vaccination during the Delta-dominant period. In both Delta and Omicron-dominant periods, homologous BNT162b2 boosting offered the highest protection against infection relative to primary BNT162b2 vaccination. This is followed by heterologous boosting with either AZD1222 or BNT162b2 for recipients primed with CoronaVac or AZD1222, and finally homologous boosting with AZD1222 and CoronaVac. The mVE estimates for all booster combinations in the Omicrondominant period was about half that of Delta. Vaccination with a primary COVID-19 vaccines were effective in reducing COVID-19 infection but wanes after 3-5 months. Additional booster doses were more effective than primary series alone in preventing COVID-19 infection but demonstrated an interplay of immune evasion during the Omicron-dominant period. Homologous BNT162b2 boosting aside, and heterologous boosting appeared to be more protective than homologous boosting. Although vaccination is still protective against severe infection, ongoing community transmission could facilitate viral mutation. Next generation, multivalent vaccines aimed at stemming transmission, are warranted.
ABSTRACT
Background: Throughout the COVID-19 pandemic, it was evident that many SARS-CoV-2 infections occurred at mass gathering events. In many LMICs and LICs, places of worship serve as a venue for mass gatherings, and therefore a potential source of large-scale transmission events. Mass gatherings at places of worship also serve as an opportunity to distribute Ag-RDTs to a significant proportion of the community at regular intervals, disrupting transmission within the event and potentially impacting community spread of SARS-CoV-2. Method(s): We used an agent-based community assessment model, Propelling Action for Testing and Treatment, to estimate how various strategies of asymptomatic Ag-RDT self-testing of a fixed percentage of persons attending large religious gatherings (10%, 20%, 40%, 100%), in addition to the general underlying level of ongoing symptomatic testing in the population, would impact community transmission of SARS-CoV-2 in 3 contexts (Brazil, Georgia, Zambia). These testing strategies were analyzed with bi-weekly and weekly asymptomatic self-testing in a population with varying levels of vaccine efficacy (low/high), vaccine coverage (10%, 50%, 80%), and reproductive numbers (0.9, 1.2, 1.5, and 2.0) to simulate varying stages of the COVID-19 pandemic. We then performed an economical evaluation of the results from the model to understand the impact and cost-effectiveness of each self-testing strategy at places of worship. Result(s): In each of the epidemic conditions modeled, testing of symptomatic persons at weekly and biweekly frequencies can avert 2%-16% of Brazilian community infections and 31%-45% of infections occurring in places of worship in Brazil. The same is true in Georgia (1%-6% of total infections and 28%-45% place of worship-related infections) and Zambia (2%-21% of total infections and 29%-45% of place of worship related infections) despite differences in the proportion of populations regularly attending places of worship in the 3 countries. Asymptomatic self-testing in 100% of places of worship in a country result in the greatest percent of infections averted and consistently lands on the cost-effectiveness frontier yet requires a budget 520- 1550x greater than that of symptomatic testing alone. Conclusion(s): Testing of symptomatic persons attending regular religious gatherings have a significant impact on the spread of SARS-CoV-2 in places of worship and can significantly reduce community spread in contexts where population level attendance at religious gatherings is high. Cost-effectiveness analysis from Brazil, Georgia and Zambia modelling results with infections averted within places of worship and total community infections averted assuming a total cost per self-test of $2.50 USD.
ABSTRACT
This research developed a multinomial classification model that predicts the prevalent mode of transmission of the coronavirus from person to person within a geographic area, using data from the World Health Organization (WHO). The WHO defines four transmission modes of the coronavirus disease 2019 (COVID-19);namely, community transmission, pending (unknown), sporadic cases, and clusters of cases. The logistic regression was deployed on the COVID-19 dataset to construct a multinomial model that can predict the prevalent transmission mode of coronavirus within a geographic area. The k-fold cross validation was employed to test predictive accuracy of the model, which yielded 73% accuracy. This model can be adopted by local authorities such as regional, state, local government, and cities, to predict the prevalent transmission mode of the virus within their territories. The outcome of the prediction will determine the appropriate strategies to put in place or re-enforced to curtail further transmission.Copyright © 2023 Inderscience Enterprises Ltd.
ABSTRACT
Background: The spread of COVID-19 was inevitable and has not spared small and isolated communities, including the community on Perhentian Island in Besut District, Terengganu. Managing clusters in small islands can be difficult, given the limited resources. This study explores the characteristics of COVID-19 cases and the experience of outbreak containment at Perhentian Island. Methodology: A retrospective study involving record review of COVID-19 cases and at-risk individuals registered under the Perhentian Cluster were retrieved from the Besut District Health Office COVID-19 online registry from the 16th August 2021 until 6th October 2021. All notified cases and close contacts who fulfilled the inclusion criteria were extracted and analysed using descriptive statistics. Result(s): A total of 1,093 out of 2,500 community members of Perhentian Island were screened of which 170 (15.5%) tested positive for COVID-19, while 923 (84.5%) tested negative. Among individuals who tested positive, the majority were adults (52.4%), males (51.8%), Malays (98.8%), and villagers (96.5%). Clinical characteristics were categorized into: asymptomatic (55.9%), had no known medical comorbidities (90.6%), low-risk groups (87.1%), vaccinated (57.6%), and admitted to PKRC (97.1%) for treatment. Multiple agencies were involved in the outbreak containment of the Perhentian Cluster, working collectively and in good coordination. Conclusion(s): The outbreak was attributed to community gatherings and close interactions among villagers. Prompt actions, targeted planning, and inter-agency collaboration were the key factors in successful containment of further spread of COVID-19 in Perhentian Island.Copyright © 2023, Faculty of Medicine, University of Malaya. All rights reserved.
ABSTRACT
Background: Anaesthetists are frontline workers who perform aerosol-generating procedures (AGPs) in enclosed environments, which exposes them to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increases their risk of contracting SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19). This study describes the prevalence of SARS-CoV-2 infection in the academic department of anaesthesiology of the University of the Witwatersrand prior to vaccination. Method(s): A cross-sectional, contextual, descriptive research design, using an anonymous electronic questionnaire, was followed in the study. Consecutive and convenience sampling methods were used. A p-value of < 0.05 was considered statistically significant. Result(s): A total of 147 participants met the inclusion criteria. There were 90 (61.22%) females and 57 (38.78%) males. The mean age was 35.26 years for the 36 participants who tested positive (26.47%) for SARS-CoV-2. Hospital admission was required by 2.78% of participants with COVID-19. Male participants had a higher prevalence of having SARS-CoV-2 infection (p = 0.045). There were no statistically significant associations between SARS-CoV-2 infection and pregnancy (p = 0.09), asthma (p = 0.11), autoimmune disease (p = 0.77), obesity (p = 0.9), diabetes (p = 0.96), hypertension (p = 0.9) and smoking (p = 0.69). Commonly reported COVID-19-like symptoms included fatigue (68.33%), headaches (61.67%) and myalgia (58.33%). Of the participants with a positive SARS-CoV-2 test, 38.46% had reported travelling within 14 days of testing positive (p < 0.001). Community exposure to a person with SARS-CoV-2 was associated with participants contracting SARS-CoV-2 infection (p = 0.001). Conclusion(s): AGPs are not a significant risk factor for anaesthetists in the context of work or community transmission of the virus. There was a statistically significant predisposition for contracting SARS-CoV-2 infection among males, participants who travelled and participants who had community exposure to a SARS-CoV-2 infected person.
ABSTRACT
Background: Coronavirus, called as, "the worst public health crisis for a generation," is a malevolent silent killer. Objective(s): One of the main concerns is containing the disease and avoiding the second wave of the pan-demic, likely to arise because of the symptomatic patients, while ensuring the safe execution of day to day tasks. Method(s): The indirect transmission of coronavirus from asymptomatic individuals during incubation time and the identification of the people who have accidentally and unknowingly come in contact with infected but asymptomatic patients pose a significant challenge to the health care providers. Result(s): Herein, for the first time, we have introduced a quantitative index;asymptomatic growth, to indicate whether the COVID-19 community spread is under control and if economic activities can be resumed. Conclusion(s): More importantly, our system provides a feasible mechanism for improving the index to a level <1, a safety level at which normal economic activities can be conducted.Copyright © 2021 Bentham Science Publishers.
ABSTRACT
Introduction: To describe the incidence and outcomes of SARS-CoV-2 infection, to evaluate its impact (mortality), and the factors associated with infection and mortality in dialysis patients in Argentina. Method(s): All prevalent dialysis patients were included from the period from April 2020 to February 2022. The positive COVID diagnosis was always made with swab and PCR. Signs and symptoms at disease onset were included, as well as the evolution of the patient that included the requirement of hospitalization, hospitalization in a care unit (ICU) and the need for invasive respiratory assistance. Continuous variables are expressed as mean +/- standard deviation or median and range, whether or not they are parametric, continuous variables are expressed as frequency and prevalence. According to the pandemic in the general population, 3 periods were considered: period 1 (Jan2020-Feb2021), period 2 (Mar2021-Nov2021), period 3 (Dec2021-Feb2022). Univariate analysis was performed for infection and mortality as dependent variables, using the T Test, Wilcoxon or Chi2 as appropriate. Multivariate analysis was performed for the dependent variable mortality. A p<0.05 was considered significant. The analysis was performed with the software MedCalc 20113. Result(s): 27,548 cases were recorded (12,221, 10,241, and 5,086 in periods 1, 2, and 3, respectively). The median age was 60.8 years (52% > 60 years) and 58% were male. The most frequent antecedents were community transmission and close contact with a suspected or confirmed case. The most frequent symptoms were malaise (16%), headaches (13%), odynophagia (10%) and myalgia (11%). The most frequent clinical signs were: cough (28%9, Tdegree >= 38degreeC (20%), dyspnoea (12%) and tachypnoea (6%). Mean time between the onset of symptoms and the PCR result of 3.8 days. Of the positive cases, 31% required hospitalization, and of these 26% were in the ICU. Of those admitted to the ICU, 50% required MV. Overall mortality was 23.4%. Mortality was higher during the first period and consequently reduced during 2nd and 3rd period (27, 2%;19, 8%;2, 9% respectively).The most frequent CKD aetiologies were DBT, unknown and nephroangiosclerosis. Most of the patients had less than 3 years on dialysis, but the highest mortality was seen in the group with more than 3 years of dialysis. COVID-19 cases were more prevalent in HD patients compared to PD patients, however the type of modality did not show differences in terms of mortality. Table 1 shows those variables associated with mortality. [Formula presented] Conclusion(s): Throughout the three periods of the COVID pandemic, a decrease in hospitalization and mortality was observed. These variables as well as the infection rate were higher than in the general population. Vaccination, a priority in this population, was associated with lower mortality. Joint actions between Public Health entities and Scientific Societies in pandemic situations ensure an adequate diagnosis of the situation and the bases for timely actions. No conflict of interestCopyright © 2023
ABSTRACT
This research developed a multinomial classification model that predicts the prevalent mode of transmission of the coronavirus from person to person within a geographic area, using data from the World Health Organization (WHO). The WHO defines four transmission modes of the coronavirus disease 2019 (COVID-19);namely, community transmission, pending (unknown), sporadic cases, and clusters of cases. The logistic regression was deployed on the COVID-19 dataset to construct a multinomial model that can predict the prevalent transmission mode of coronavirus within a geographic area. The k-fold cross validation was employed to test predictive accuracy of the model, which yielded 73% accuracy. This model can be adopted by local authorities such as regional, state, local government, and cities, to predict the prevalent transmission mode of the virus within their territories. The outcome of the prediction will determine the appropriate strategies to put in place or re-enforced to curtail further transmission.
ABSTRACT
Communicable disease pandemic is a severe disease outbreak all over the countries and continents. Swine Flu, HIV/AIDS, corona virus disease-19 (COVID-19), etc., are some of the global pandemics in the world. The major cause of becoming pandemic is community transmission and lack of social distancing. Recently, COVID-19 is such a largest outbreak all over the world. This disease is a communicable disease which is spreading fastly due to community transmission, where the affected people in the community affect the heathy people in the community. Government is taking precautions by imposing social distancing in the countries or state to control the impact of COVID-19. Social distancing can reduce the community transmission of COVID-19 by reducing the number of infected persons in an area. This is performed by staying at home and maintaining social distance with people. It reduces the density of people in an area by which it is difficult for the virus to spread from one person to other. In this work, the community transmission is presented using simulations. It shows how an infected person affects the healthy persons in an area. Simulations also show how social distancing can control the spread of COVID-19. The simulation is performed in GNU Octave programming platform by considering number of infected persons and number of healthy persons as parameters. Results show that using the social distancing the number of infected persons can be reduced and heathy persons can be increased. Therefore, from the analysis it is concluded that social distancing will be a better solution of prevention from community transmission.
ABSTRACT
The spread of COVID-19 at a large scale and at a rapid pace indicates the lack of social distancing measures at multiple levels. The individuals are not to be blamed, nor should we assume the early measures were ineffective or not implemented. It is all down to the multiplicity of transmission factors that made the situation more complicated than initially anticipated. Therefore, in facing the COVID-19 pandemic, this overview paper discusses the importance of space in social distancing measures. The methods used to investigate this study are literature review and case study. Many scholarly works have already provided us with evidence-based models that suggest the influential role of social distancing measures in preventing COVID-19 community spread. To further elaborate on this important topic, the aim here is to look at the role of space not only at the individual level but at larger scales of communities, cities, regions, etc. The analysis helps better management of cities during the pandemics such as COVID-19. By reflecting on some of the ongoing research on social distancing, the study concludes with the role of space at multiple scales and how it is central to the practice of social distancing. We need to be more reflective and responsive to achieve earlier control and containment of the disease and the outbreak at the macro level.
ABSTRACT
Community transmission of SARS-CoV-2 in densely populated countries has been a topic of concern from the beginning of the pandemic. Evidence of community transmission of SARS-CoV-2 according to population density gradient and socio-economic status (SES) is limited. In June-September 2020, we conducted a descriptive longitudinal study to determine the community transmission of SARS-CoV-2 in high- and low-density areas in Dhaka city. The Secondary Attack Rate (SAR) was 10% in high-density areas compared to 20% in low-density areas. People with high SES had a significantly higher level of SARS-CoV-2-specific Immunoglobulin G (IgG) antibodies on study days 1 (p = 0.01) and 28 (p = 0.03) compared to those with low SES in high-density areas. In contrast, the levels of seropositivity of SARS-CoV-2-specific Immunoglobulin M (IgM) were comparable (p > 0.05) in people with high and low SES on both study days 1 and 28 in both high- and low-density areas. Due to the similar household size, no differences in the seropositivity rates depending on the population gradient were observed. However, people with high SES showed higher seroconversion rates compared to people with low SES. As no difference was observed based on population density, the SES might play a role in SARS-CoV-2 transmission, an issue that calls for further in-depth studies to better understand the community transmission of SARS-CoV-2.
ABSTRACT
HYPOTHESIS: The formation of virus-laden colloidal respiratory microdroplets - the sneeze or cough virulets and their evaporation driven miniaturization in the open air are found to have a significant impact on the community transmission of COVID-19 pandemic. SIMULATION DETAILS: We simulate the motions and trajectories of virulets by employing laminar fluid flow coupled with droplet tracing physics. A force field analysis has been included considering the gravity, drag, and inertial forces to unleash some of the finer features of virulet trajectories leading to the droplet and airborne transmissions of the virus. Furthermore, an analytical model corroborates temperature (T) and relative humidity (RH) controlled droplet miniaturization. RESULTS: The study elucidates that the tiny (1-50 µm) and intermediate (60-100 µm) size ranged virulets tend to form bioaerosol and facilitate an airborne transmission while the virulets of larger dimensions (300 to 500 µm) are more prone to gravity dominated droplet transmission. Subsequently, the mapping between the T and RH guided miniaturization of virulets with the COVID-19 cases for six different cities across the globe justifies the significant contribution of miniaturization-based bioaerosol formation for community transmission of the pandemic.
Subject(s)
COVID-19 , Cough , Humans , Pandemics , Physical Phenomena , SneezingABSTRACT
A COVID-19 cluster was identified in an industrial manufacturing workforce soon after being recalled to the workplace following a furlough period. All cases in the cluster (21/85) were male, worked on one side of the plant, and took breaks and lunch together. All non-cases worked on the opposite side of the plant and similarly took breaks and lunch together. Review of the timing of return from furlough determined that workplace transmission was possible. However, a high percentage of the cases lived in apartment settings where high neighbourhood incidence rates were observed, whereas that was not the case for non-cases. The investigation illustrates the difficulties of distinguishing potential occupational from community transmission.
ABSTRACT
Background: Knowing the prevalence of true asymptomatic coronavirus disease 2019 (COVID-19) cases is critical for designing mitigation measures against the pandemic. We aimed to synthesize all available research on asymptomatic cases and transmission rates. Methods: We searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC for primary studies on asymptomatic prevalence in which (1) the sample frame includes at-risk populations, and;(2) follow-up was sufficient to identify pre-symptomatic cases. Meta-analysis used fixed-effects and random-effects models. We assessed risk of bias by combination of questions adapted from risk of bias tools for prevalence and diagnostic accuracy studies. Results: We screened 2,454 articles and included 13 low risk-of-bias studies from seven countries that tested 21,708 at-risk people, of which 663 were positive and 111 asymptomatic. Diagnosis in all studies was confirmed using a real-time reverse transcriptase–polymerase chain reaction test. The asymptomatic proportion ranged from 4% to 41%. Meta-analysis (fixed effects) found that the proportion of asymptomatic cases was 17% (95% CI 14% to 20%) overall and higher in aged care (20%;95% CI 14% to 27%) than in non-aged care (16%;95% CI 13% to 20%). The relative risk (RR) of asymptomatic transmission was 42% lower than that for symptomatic transmission (combined RR 0.58;95% CI 0.34 to 0.99, p = 0.047). Conclusions: Our one-in-six estimate of the prevalence of asymptomatic COVID-19 cases and asymptomatic transmission rates is lower than those of many highly publicized studies but still sufficient to warrant policy attention. Further robust epidemiological evidence is urgently needed, including in subpopulations such as children, to better understand how asymptomatic cases contribute to the pandemic.