Control COVID-19 Spread Research Articles

Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: a modelling study using mobile phone data

BackgroundRestricting human mobility is an effective strategy used to control disease spread. However, whether mobility restriction is a proportional response to control the ongoing COVID-19 pandemic is unclear. We aimed to develop a model that can quantify the potential effects of various intracity mobility restrictions on the spread of COVID-19.MethodsIn this modelling study, we used anonymous and aggregated mobile phone sightings data to build a susceptible–exposed–infectious–recovered transmission model for COVID-19 based on the city of Shenzhen, China. We simulated how disease spread changed when we varied the type and magnitude of mobility restrictions in different transmission scenarios, with variables such as the basic reproductive number (R0), length of infectious period, and the number of initial cases.Findings331 COVID-19 cases distributed across the ten regions of Shenzhen were reported on Feb 7, 2020. In our basic scenario (R0 of 2·68), mobility reduction of 20–60% within the city had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases by 33% (95% UI 21–42) and delay to the peak number by 2 weeks with a 20% restriction, 66% (48–75) reduction and 4 week delay with a 40% restriction, and 91% (79–95) reduction and 14 week delay with a 60% restriction. The effects of mobility restriction were increased when combined with reductions of 25% or 50% in transmissibility of the virus. In specific analyses of mobility restrictions for individuals with symptomatic infections and for high-risk regions, these measures also had substantial effects on reducing the spread of COVID-19. For example, the peak of the epidemic was delayed by 2 weeks if the proportion of individuals with symptomatic infections who could move freely was maintained at 20%, and by 4 weeks if two high-risk regions were locked down. The simulation results were also affected by various transmission parameters.InterpretationOur model shows the effects of various types and magnitudes of mobility restrictions on controlling COVID-19 outbreaks at the city level in Shenzhen, China. The model could help policy makers to establish the optimal combinations of mobility restrictions during the COVID-19 pandemic, especially to assess the potential positive effects of mobility restriction on public health in view of the potential negative economic and societal effects.FundingGuangdong Medical Science Fund, and National Natural Science Foundation of China.

Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modelling Approach

The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10 concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.

Impact of COVID-19 Pandemic on Labor Supply and Gross Value Added in India

This paper estimates the first order supply shock through labour supply reduction associated with the containment measures taken by the Government of India to control COVID-19 spread. We make use of two metrics to estimate the labour supply shock. The first metric is based on whether a worker is employed in an essential or a non-essential industry and second measures the extent to which a worker can perform the work activities remotely. For the latter, we construct a Remote Labour Index (RLI) following Rio-Chanona et al. (2020). Using PLFS (2017-18) we find that 116.18 million (25 percent) and 78.93 million (17 percent) workers were affected in Lockdown 1.0 and Lockdown 2.0, respectively, and are at risk of job loss. To get an extensive impact of COVID-19 pandemic on the labour market in India we carry out an in-depth analysis of labour supply shocks by employment status, industry level, and occupation. The expected monthly wage loss of casual workers and regular and salaried employees is estimated to be Rs. 33.8 thousand crores (in 2017-18 prices). Further, the loss in Gross Value Added (GVA) (at 2011-12 prices) is predicted to be between 13 percent and 19 percent during the lockdown period from 25th March to 31st May 2020. The y-o-y quarterly growth rate forecast of GVA (at 2011-12 prices) for Q1:2020-21 is expected to be between -4.6 percent and -8.8 percent, using the baseline model.

Covid-19 risk assessment in public transport using ambient sensor data and wireless communications

Covid-19 causes one of the most alarming global health and economic crises in modern times. Countries around the world establish different preventing measures to stop or control Covid-19 spread. The goal of this paper is to present methods for the evaluation of indoor air quality in public transport to assess the risk of contracting Covid19. The first part of the paper involves investigating the relationship between Covid-19 and various factors affecting indoor air quality. The focus of this paper relies on exploring existing methods to estimate the number of occupants in public transport. It is known that increased occupancy rate increases the possibility of contamination as well as indoor carbon dioxide concentration. Wireless data collection schemes will be defined that can collect data from public transportation. Collected data are envisioned to be stored in the cloud for data analytics. We will present novel methods to analyze the collected data by considering the historical data and estimate the virus contagion risk level for each public transportation vehicle in service. The methodology is expected to be applicable for other airborne diseases as well. Real-time risk levels of public transportation vehicles will be available through a mobile application so that people can choose their mode of transportation accordingly.

An Automated Contact Tracing Approach for Controlling Covid-19 Spread Based on Geolocation Data From Mobile Cellular Networks.

The coronavirus (COVID-19) has appeared as the greatest challenge due to its continuous structural evolution as well as the absence of proper antidotes for this particular virus. The virus mainly spreads and replicates itself among mass people through close contact which unfortunately can happen in many unpredictable ways. Therefore, to slow down the spread of this novel virus, the only relevant initiatives are to maintain social distance, perform contact tracing, use proper safety gears, and impose quarantine measures. But despite being conceptually possible, these approaches are very difficult to uphold in densely populated countries and areas. Therefore, to control the virus spread, researchers and authorities are considering the use of smartphone based mobile applications (apps) to identify the likely infected persons as well as the highly risky zones to maintain isolation and lockdown measures. However, these methods heavily depend on advanced technological features and expose significant privacy loopholes. In this article, we propose a new method for COVID-19 contact tracing based on mobile phone users’ geolocation data. The proposed method will help the authorities to identify the number of probable infected persons without using smartphone based mobile applications. In addition, the proposed method can help people take the vital decision of when to seek medical assistance by letting them know whether they are already in the list of exposed persons. Numerical examples demonstrate that the proposed method can significantly outperform the smartphone app-based solutions.

Knowledge, attitude, practices and behaviour study regarding COVID-19 amongst health care workers of armed forces in North-Western part of India

Background: A concerted effort has been made by the Government of India and the Armed Forces to train all health-care workers (HCWs) in various aspects of the prevention and management of COVID-19. This study was conducted to evaluate the efforts by assessing their knowledge, attitudes, practice, and behavior regarding COVID-19. Materials and Methods: A quick online survey, using a web portal and social media platform with a pretested questionnaire, was conducted. Responses were collected for 3 days and analyzed. Results: A total of 988 HCWs participated, including 61 (6.17%) specialist officers, 98 (9.91%) medical officers, 17 (1.72%) dental officers, 135 (13.66%) nursing officers, 518 (52.4%) paramedical staff, and 159 (16.09%) supporting staff. There was a high prevalence (>90%) of knowledge related to symptoms and transmission of the disease with no statistically significant difference in knowledge based on the category of HCW except for bleaching powder requirement (0.001) and chemoprophylaxis (0.001). The majority of the participants (>95%) agreed that lockdown, infection control programs, and repeated training of HCWs are good measures to control COVID-19 spread. Observing full precaution while handling personal protective equipment was the only practice which demonstrated a significant association with increasing qualification of the participant (P

Has it done properly? The Difference between Before and After Social Distancing’s Policy Implementation in Controlling Covid-19 in Jakarta, Indonesia

Social distancing shall be effective to control Covid-19 spread. However, its effectiveness is doubtfully due to late response of authority in a low-resource setting such as Indonesia. This study aims to present the effectiveness of large-sale social restriction (LSSR) as the social distancing policy by analyze the chronological as well as the difference between before and after LSSR implementation in Jakarta, Indonesia. The secondary data analysis was derived from surveillance data for Covid-19 from government authorities, including the Ministry of Health and the local government of Jakarta. Two statuses related to Covid-19 were examined in the study: incidence and suspect. These Covid-19 statuses were presented in daily rates with pre and post of LSSR policy in Jakarta, Indonesia. LSSR policy had just implemented over a month after the first multiple cases found. The number of positive confirmed patients increased significantly after the LSSR (p-value = 0.000; mean difference = -70.532). This study’s findings showed that social distancing was not effective to control Covid-19 incidence which indicates the late response of the authorities.

Estimating healthcare resource needs for COVID-19 patients in Nigeria.

Introductioncontinuous assessment of healthcare resources during the COVID-19 pandemic will help in proper planning and to prevent an overwhelming of the Nigerian healthcare system. In this study, we aim to predict the effect of COVID-19 on hospital resources in Nigeria.Methodswe adopted a previously published discrete-time, individual-level, health-state transition model of symptomatic COVID-19 patients to the Nigerian healthcare system and COVID-19 epidemiology in Nigeria by September 2020. We simulated different combined scenarios of epidemic trajectories and acute care capacity. Primary outcomes included the expected cumulative number of cases, days until depletion resources and the number of deaths associated with resource constraints. Outcomes were predicted over a 60-day time horizon.Resultsin our best-case epidemic trajectory, which implies successful implementation of public health measures to control COVID-19 spread, assuming all three resource scenarios, hospital resources would not be expended within the 60-days time horizon. In our worst-case epidemic trajectory, assuming conservative resource scenario, only ventilated ICU beds would be depleted after 39 days and 16 patients were projected to die while waiting for ventilated ICU bed. Acute care resources were only sufficient in the three epidemic trajectory scenarios when combined with a substantial increase in healthcare resources.Conclusionsubstantial increase in hospital resources is required to manage the COVID-19 pandemic in Nigeria, even as the infection growth rate declines. Given Nigeria's limited health resources, it is imperative to focus on maintaining aggressive public health measures as well as increasing hospital resources to reduce COVID-19 transmission further.

G.P. Filing System

<h3>Abstract</h3> <h3>Background</h3> The ability of countries to contain and control COVID-19 virus transmission via social distancing is critical in the absence of a vaccine. Early activation of robust measures has been shown to control the daily infection rate, and consequential pressure on the health care system. As countries begin to control COVID-19 spread an understanding of how to ease social distancing measures to prevent a rebound in cases and deaths is required. <h3>Methods</h3> Using COVID-19 transmission data from the outbreak source in Hubei Province, China prior to activation of containment measures, we adapted an established individual-based simulation model of the city of Newcastle, Australia. Simulation of virus transmission in this model, with and without, social distancing measures activated permitted us to quantify social distancing effectiveness. Optimal strategies for relaxing social distancing were determined under two settings: with high numbers of daily cases, as in New York; and where early social distancing activation resulted in limited ongoing transmission, as in Perth, Australia. <h3>Findings</h3> In countries where strong social distancing measures were activated after the COVID-19 virus had spread widely, our study found these measures are required to be maintained for significant periods before being eased, to return to a situation where daily case numbers become low. In countries where early responses to the COVID-19 pandemic have been highly successful, as in Australia, we show that a staged relaxation of social distancing prevents a rebound in cases. <h3>Interpretation</h3> Modelling studies and direct observation have shown that robust and timely social distancing have the most effect in containing the spread of the COVID-19 virus. Questions arise as to the duration of strong social distancing measures, given they are highly disruptive to society and economic activity. This study demonstrates the necessity of holding robust social distancing in place until COVID-19 virus transmission has significantly decreased, and how they may then be safely eased.