Regional Lockdown Research Articles

Spatial spread of COVID-19 during the early pandemic phase in Italy

Quantifying the potential spatial spread of an infectious pathogen is key to defining effective containment and control strategies. The aim of this study is to estimate the risk of SARS-CoV-2 transmission at different distances in Italy before the first regional lockdown was imposed, identifying important sources of national spreading. To do this, we leverage on a probabilistic model applied to daily symptomatic cases retrospectively ascertained in each Italian municipality with symptom onset between January 28 and March 7, 2020. Results are validated using a multi-patch dynamic transmission model reproducing the spatiotemporal distribution of identified cases. Our results show that the contribution of short-distance (≤10km)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\le 10 km)$$\\end{document} transmission increased from less than 40% in the last week of January to more than 80% in the first week of March 2020. On March 7, 2020, that is the day before the first regional lockdown was imposed, more than 200 local transmission foci were contributing to the spread of SARS-CoV-2 in Italy. At the time, isolation measures imposed only on municipalities with at least ten ascertained cases would have left uncontrolled more than 75% of spillover transmission from the already affected municipalities. In early March, national-wide restrictions were required to curb short-distance transmission of SARS-CoV-2 in Italy.

The Causes of Stress on Elderly During Pandemic of Covid-19: A Systematic Review

The problem of COVID-19 was able to infect all people regardless of age group, however the elderly of 60 years and above were the more vulnerable population to exposure to the corona virus. This research was aimed to identify the causes of stress on elderly during pandemic of COVID-19. Methods: A systematic search through three databases: ScienceDirect, PubMed, and ProQuest, by using these following terms “causes of psychological”, “stress”, “cause”, “elderly”, “older adult”, and “COVID-19”. The search was restricted on publication during December 2019 – October 2020. The article was selected by exerting PRISMA, the total of 16 articles were analyzed through systematic review. Findings: Based on the synthetic finding, this research found that the stress on elderly was divided into two factors. The internal factors were chronic disease, loneliness, emotional condition, and self-endurance, while external factor were lack of family support, regional lockdown, lack of communication with neighbor, reduced income, and lack of physical exercise. Conclusions: This research finding referred to risk factors from wither internal factor or external factor which could cause the stress on elderly during this pandemic of COVID-19.

Quantifying the Effect of Quarantine Control and Optimizing Its Cost in COVID-19 Pandemic.

The novel coronavirus has been spreading worldwide and emerged as a public health crisis. As the rapid rise of infected population count, a wide variety of stringent non-pharmaceutical interventions have been taken by cities and countries around the globe, including mobility reduction, social distancing and regional lockdown. The efficacy of these interventions is hard to quantify as individuals violate policies, travel inadvertently or deliberately, and spread the virus without themselves being infected. Furthermore, the publicly available pandemic data on infectious rates and other epidemiological data are unreliable and limited, and are even underestimated. In this paper, we intend to interpret and forecast the spreading dynamics of Covid-19 and quantify the efficacy of quarantine control adopted by Wuhan, Italy, South Korea and the United States of America, employing a hybrid model of an epidemiological model and a data-driven neural network model. Furthermore, since the Covid-19 has prompted global travel restrictions, aggravated unemployment, and influenced the global economy, which exemplify the great societal cost of interventions in the battle of halting Covid-19 spreading. We intend to develop optimal quarantine control under which the tradeoff between Covid-19 containment and the societal cost of quarantine control can be optimized. Optimal quarantine control enables communities have opportunities to catch their breath to reserve healthcare resources preemptively, while the Covid-19 spreading can be halted. Our results unequivocally indicate that governments that taken stringent interventions starting from the initial stage can efficiently halt the spreading of Covid-19; furthermore, the total societal cost of such interventions is greatly smaller.

The Impact of COVID-19 on the Neck of Femur Fracture Service in a Tertiary Care Hospital in the United Kingdom.

Introduction The emergence of the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in late 2019 ushered in a global crisis that profoundly impacted healthcare systems worldwide. In the United Kingdom, COVID-19 resulted in a significant toll on public health and the National Health Service (NHS). As the virus surged, the NHS faced unprecedented challenges, including surges in COVID-19 cases, a dire need for medical equipment, and a strain on intensive care units. Simultaneously, stringent nationwide lockdowns were imposed to curb the virus's spread, disrupting daily life and healthcare access. Amid this crisis, the interactions between COVID-19 and other prevalent health conditions came to the forefront of medical research, sparking interest in understanding their connections. This study delves into the intriguing interplay between COVID-19 and neck of femur (NoF) fractures, exploring shared risk factors, resource implications, and potential alterations in patient pathways. Given the severity of both conditions and their impact on the vulnerable elderly population, elucidating these connections is crucial for comprehensive patient care and resource allocation within the healthcare system. Methods This study used data from the National Hip Fracture Audit (NHFA) database, focusing on NoF fracture patients at Wythenshawe Hospital. We examined two cohorts: pre-pandemic (from March 2019 to March 2020) and pandemic (from March 2020 to March 2021). We compared key parameters and incorporated COVID-19 data. Graphs showed trends and cohort similarities. We also analyzed demographic data (age, gender, fracture type, times, COVID-19 status, and mortality), removing outliers for accuracy. Results The data revealed that while certain factors such as patient age and mobilization remained largely unaffected, there was a modest association between COVID-19 incidence and NoF fracture patients. Notably, regional lockdown measures had a substantial impact on patient care. The initial lockdown effectively reduced COVID-19-positive cases upon admission but led to prolonged intervals and surgical delays. However, the second lockdown showed improvements, attributed to lessons learned, increased resource allocation, and better familiarity with hospital-specific lockdown measures. This research sheds light on the intricate relationship between a global pandemic and orthopedic patient care, highlighting the importance of adapting healthcare systems to evolving challenges. Conclusion This study explores the impact of COVID-19 on neck of femur (NoF) fracture patients, highlighting key findings from Wythenshawe Hospital. It uncovers a dynamic relationship between the pandemic and patient care, with increased COVID-19 cases coinciding with reduced NoF fracture rates. Lockdowns influenced outcomes, with the first causing delays and higher post-discharge mortality, while the second improved efficiency and safety. These insights extend beyond Wythenshawe Hospital, offering implications for healthcare practices in the United Kingdom and beyond, especially in countries with limited vaccination resources. This research underscores the need for tailored strategies to optimize NoF fracture patient outcomes during pandemics and lockdowns.

EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control.

The outbreak of coronavirus disease (COVID-19) has swept across more than 180 countries and territories since late January 2020. As a worldwide emergency response, governments have implemented various measures and policies, such as self-quarantine, travel restrictions, work from home, and regional lockdown, to control the spread of the epidemic. These countermeasures seek to restrict human mobility because COVID-19 is a highly contagious disease that is spread by human-to-human transmission. Medical experts and policymakers have expressed the urgency to effectively evaluate the outcome of human restriction policies with the aid of big data and information technology. Thus, based on big human mobility data and city POI data, an interactive visual analytics system called Epidemic Mobility (EpiMob) was designed in this study. The system interactively simulates the changes in human mobility and infection status in response to the implementation of a certain restriction policy or a combination of policies (e.g., regional lockdown, telecommuting, screening). Users can conveniently designate the spatial and temporal ranges for different mobility restriction policies. Then, the results reflecting the infection situation under different policies are dynamically displayed and can be flexibly compared and analyzed in depth. Multiple case studies consisting of interviews with domain experts were conducted in the largest metropolitan area of Japan (i.e., Greater Tokyo Area) to demonstrate that the system can provide insight into the effects of different human mobility restriction policies for epidemic control, through measurements and comparisons.

Estimating the propagation of both reported and undocumented COVID-19 cases in Spain: a panel data frontier approximation of epidemiological models.

We use a stochastic frontier analysis (SFA) approach to model the propagation of the COVID-19 epidemic across geographical areas. The proposed models permit reported and undocumented cases to be estimated, which is important as case counts are overwhelmingly believed to be undercounted. The models can be estimated using only epidemic-type data but are flexible enough to permit these reporting rates to vary across geographical cross-section units of observation. We provide an empirical application of our models to Spanish data corresponding to the initial months of the original outbreak of the virus in early 2020. We find remarkable rates of under-reporting that might explain why the Spanish Government took its time to implement strict mitigation strategies. We also provide insights into the effectiveness of the national and regional lockdown measures and the influence of socio-economic factors in the propagation of the virus.

Modeling the impact of national and regional lockdowns on the 2020 spring wave of COVID-19 in France

Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like “where” and “when” still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increase. However, the public health costs associated with these delays tend to grow with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality, and stress on the healthcare system.

Variations in local, transported, and exposure risks of PM2.5 pollution: Insights from long-term monitoring data in mega coastal city

Urban air quality is influenced by both local and external sources of pollution. The outbreak of Coronavirus COVID-19 had led to implementation of stringent lockdowns at different levels of governance. National Level Lockdown (NLL) was imposed in 2020 and State Level Lockdown (SLL), in 2021 to curb the spread of disease. A direct consequence of lockdown is the dramatic improvement of air quality in various urban agglomerations. The present study investigated the effects of national and regional lockdown on PM2.5 levels at various urban morphological units in the Chennai Metropolitan Region, the fourth-largest urban conglomeration in India. Hourly measurements of PM2.5 over a 6-year period (2016–2021) at three monitoring sites in Chennai were segregated into Pre-lockdown Phase (PLP) (2016–2019), NLL, and SLL to analyze reductions in PM2.5 levels. Local PM2.5 sources were investigated using Conditional Bivariate Probability Function (CBPF) whereas transported PM2.5 was evaluated using Concentration Weighted Trajectory (CWT) and Cluster Analysis. The results showed that PM2.5 in Chennai Metropolitan Region reduced by 33.45% during NLL and 48.95% during SLL when compared to PLP. Mann Kendall Test showed a statistically significant (p < .001) decreasing PM2.5 trend at Manali Monitoring Site, Alandur Monitoring Site, and Velachery Monitoring Site. CBPF showed variations in local contributions for all sites during the selected time frames. CWT and Cluster analysis showed reductions in transported PM2.5 during NLL and SLL when compared to PLP. Health Risk Assessment using Integrated Exposure Response (IER) model function showed a decreasing trend of excess mortality for various health endpoints over 6-year period. Steep reductions in excess mortality cases were observed during NLL and SLL. The results show that lockdown implemented at the state level proved to be more effective than the national level in reducing PM2.5 levels over Chennai metropolitan Region.

Evaluating aerosols concentration and air quality of Indian urban agglomerations over nationwide and regional lockdown

In the past two years, numerous researches are done on how lockdowns across the world affected air quality; however, less research is done on how geolocation, geo-climate, anthropogenic activities had such impacts. National and regional shutdowns at various lockdown phases are crucial for evaluating such impacts. The goal of the current study was to examine the effects of geographic location, geo-climate, and human activity on Particulate Matter (PM10 and PM2.5) concentration and air quality about COVID-19-induced lockdowns of Mumbai and Delhi, two economically significant megacities in India with contrasting climatic conditions. Based on the incidents where restricted economic activity led to lockdowns, the importance of meteorological and economic activity in controlling air quality was evaluated. To understand spatial distribution, variability, trend, consistency analysis and National Air Quality Index (NAQI) of PM10 and PM2.5 data were collected from the Central Pollution Control Board (CPCB) monitoring system. To account for variation in various urban morphological units and gauge their responses, dispersion analysis was used. Kernel Density Estimation (KDE) plots were used to study how PM affected NAQI. From the analysis, it was clear that (1) nationwide lockdown was more fruitful in Delhi while regional lockdown in Mumbai since air quality improvement rate was substantially high in Mumbai in regional lockdown, 2021, (2) Mumbai city maritime location and long open sea coast help to reduce pollution levels while Delhi's continental location is crucial for being higher pollution levels, (3) control of meteorological factors was not found very significant, however, it was found relatively greater in Delhi, (4) air quality was found to be extremely poor in industrial and commercial areas during unlocking periods, but sensitively greater improvement was also found during lockdown periods, indicating crucial anthropogenic impact on air quality, and (5) rate of air quality improvement was highly correlated with different economic contributors. As a result, this study came to the conclusion that conditions with controlled demand can improve the air quality.

Mental health and wellbeing among people with informal caring responsibilities across different time points during the COVID-19 pandemic: a population-based propensity score matching analysis.

Due to a prolonged period of national and regional lockdown measures during the coronavirus (COVID-19) pandemic, there has been an increase reliance on informal care for informal carers. In light of this, the current study compared the experiences of carers and non-carers on various mental health and wellbeing measures across six key time points during the pandemic. Data analysed were from the University College London (UCL) COVID -19 Social Study. Our study focused on six time points in England: (1) the first national lockdown (March-April 2020); (2) the beginning of first lockdown rules easing (May 2020); (3) the second national lockdown (November 2020); (4) the third national lockdown (January 2021); (5) the easing of the third lockdown (March 2021); and (6) the end of restrictions (July-August 2021). We considered five mental health and wellbeing measures: depressive symptoms, anxiety symptoms, loneliness, life satisfaction, and sense of being worthwhile. Propensity score matching was applied for the analyses. We found that informal carers experienced higher levels of depressive and anxiety symptoms than non-carers across much of the pandemic. During the first national lockdown, carers also experienced a higher sense of life being worthwhile. No association was found between informal caring responsibilities and levels of loneliness and life satisfaction. Given that carers are an essential national healthcare support, especially during a pandemic, it is crucial to integrate carers' needs into healthcare planning and delivery. These results highlight that there is a pressing need to provide adequate and targeted mental health support for carers during and following this pandemic.

Association of national and regional lockdowns with COVID-19 infection rates in Pune, India

Assessing the impact of lockdowns on COVID-19 incidence may provide important lessons for management of pandemic in resource-limited settings. We examined growth of incident confirmed COVID-19 patients before, during and after lockdowns during the first wave in Pune city that reported the largest COVID-19 burden at the peak of the pandemic. Using anonymized individual-level data captured by Pune’s public health surveillance program between February 1st and September 15th 2020, we assessed weekly incident COVID-19 patients, infection rates, and epidemic curves by lockdown status (overall and by sex, age, and population density) and modelled the natural epidemic using the compartmental model. Effect of lockdown on incident patients was assessed using multilevel Poisson regression. We used geospatial mapping to characterize regional spread. Of 241,629 persons tested for SARS-CoV-2, 64,526 (26%) were positive, contributing to an overall rate of COVID-19 disease of 267·0 (95% CI 265·3–268·8) per 1000 persons. The median age of COVID-19 patients was 36 (interquartile range [IQR] 25–50) years, 36,180 (56%) were male, and 9414 (15%) were children < 18 years. Epidemic curves and geospatial mapping showed delayed peak of the patients by approximately 8 weeks during the lockdowns as compared to modelled natural epidemic. Compared to a subsequent unlocking period, incident COVID-19 patients were 43% lower (IRR 0·57, 95% CI 0·53–0·62) during India’s nationwide lockdown and were 22% lower (IRR 0·78, 95% CI 0.73–0.84) during Pune’s regional lockdown and was uniform across age groups and population densities. Both national and regional lockdowns slowed the COVID-19 infection rates in population dense, urban region in India, underscoring its impact on COVID-19 control efforts.

Measuring Pandemic and Lockdown Impacts on Wellbeing.

With the onset of the COVID‐19 pandemic, New Zealand's official statistical agency (Stats NZ) moved quickly to supplement the quarterly Household Labour Force Survey with wellbeing measures from the General Social Survey. The first supplement (June 2020) began toward the end of a restrictive national lockdown. Subsequent quarterly surveys continued through a second lockdown for the Auckland region, enabling tests of regional lockdown impacts. Survey measures include questions on life satisfaction, health, income adequacy, social capital (trust), and loneliness. Published aggregated data indicate that life satisfaction, social capital, health, and financial wellbeing were each higher through the pandemic (in 2020) than prior to it, including for disadvantaged groups, but loneliness rose. Analysis of the individual‐level data, confined to the within‐pandemic period, however indicates that more restrictive lockdowns were associated both with reduced life satisfaction and greater loneliness, with differing impacts according to labor market and household status.

COVID‐19 did not result in increased hospitalization for stroke and transient ischemic attack: A nationwide study

BackgroundThe risk of thrombosis increases in infectious diseases, yet observational studies from single centers have shown a decrease in admission of acute ischemic stroke patients during the COVID‐19 pandemic. To investigate unselected stroke admission rates we performed a nationwide study in Denmark.MethodsWe extracted information from Danish national health registries. The following mutually exclusive time periods were compared to the year before the lockdown: (1) first national lockdown, (2) gradual reopening, (3) few restrictions, (4) regional lockdown, and (5) second national lockdown.ResultsGenerally, admission rates were unchanged during the pandemic. In the unadjusted data, we observed a small decrease in the admission rate for all strokes under the first lockdown (incidence rate ratio: 0.93, confidence interval [CI]: 0.87–0.99) and a slight increase during the periods with gradual reopening, few restrictions, and the regional lockdown driven by ischemic strokes. We found no change in the rate of severe strokes, mild strokes, or 30‐day mortality. An exception was the higher mortality for all strokes during the first lockdown (risk ratio: crude 1.30 [CI: 1.03–1.59]; adjusted 1.17 [CI: 0.93–1.47]). The quality of care remained unchanged.ConclusionStroke admission rates remained largely unchanged during the pandemic, while an increased short‐term mortality rate in patients admitted with stroke observed during the first lockdown was seen, probably reflecting that the more frail patients constituted a higher proportion of admitted patients at the beginning of the pandemic.

Term Neonatal Complications During the Second Localized COVID-19 Lockdown and Prolonged Premature Rupture of Membranes at Home Among Nulliparas With Reference Interval for Maternal C-Reactive Protein: A Retrospective Cohort Study.

ObjectiveThe COVID-19 lockdown extended premature rupture of membranes (PROM) expectant time among nulliparas and increased the risk of term neonatal complications. This study investigated the impact of term nulliparas with PROM delays at home on neonatal outcomes during the COVID-19 lockdown period, considering the clinical diagnostic application of maternal C-reactive protein (CRP).MethodsThis study collected 505 term nulliparous women who underwent PROM at home from five provinces in a non-designated hospital of China in 2020. We analyzed PROM maternal information at home and neonatal complications in the COVID-19 regional lockdown and compared related information in the national lockdown. Poisson regression models estimated the correlation of PROM management at home, maternal CRP, and neonatal morbidity. We constructed two diagnostic models: the CRP univariate model, and an assessed cut-off value of CRP in the combined model (CRP with PROM waiting time at home).ResultsIn the regional lockdown, PROM latency at home and the severity of neonatal complications were extended and increased lower than in the nationwide lockdown, but term neonatal morbidity was not reduced in the COVID-19 localized lockdown. Prolonged waiting time at home (≥8.17 h) was associated with increasing maternal CRP values and neonatal morbidity (adjusted risk ratio 2.53, 95% CI, 1.43 to 4.50, p for trend <0.001) in the regional lockdown period. In the combined model, CRP ≥7 mg/L with PROM latency ≥8.17 h at home showed higher diagnostic sensitivity and AUC than only CRP for initial assessing the risk of adverse neonatal complications in COVID-19 regional lockdowns (AUC, 0.714 vs. 0.534; sensitivity, 0.631 vs. 0.156).ConclusionThe impact of the acute COVID-19 national blockade on the PROM newborns' health could continue to the COVID-19 easing period. Maternal CRP reference interval (≥7 mg/L) would effectively assess the risk of term neonatal morbidity when nulliparas underwent prolonged PROM expectant at home (≥8.17 h) during the second COVID-19 lockdown.

Analysis of Motor Vehicle Accidents: Comparison Between Before and During the COVID-19 Lockdown in Maharashtra, India.

To prevent the pandemic spread of human-to-human transmitted diseases such as COVID-19, governments commonly resort to countrywide or regional lockdown strategies. Such lockdowns, whenever and wherever implemented, curtail the movement of persons and vehicles, and drastically alter traffic conditions. This study focuses on the effect of drastic and sudden changes in the traffic conditions, during the COVID-19 lockdown in the State of Maharashtra in India, in March-June 2020, on the numbers of motor vehicle accidents (MVAs), and the resultant fatalities and injuries. Content analysis of police-reported first information reports (FIRs) of MVAs is performed, and these lockdown trends are compared with archival data from corresponding previous (normal) periods. The statistical analysis shows that, during the lockdown, while the total number of MVAs fall drastically, they are more severe and have a much higher fatality rate per MVA. Also, the pattern of vehicles involved in MVAs, and resultant pattern of fatalities, also changes during lockdowns. The paper explores the reasons for these changed patterns and provides suggestions to reduce these negative externalities of pandemic related lockdowns.

Can COVID-19 pandemic change plastic contamination? The Case study of seven watercourses in the metropolitan city of Milan (N. Italy)

The more or less extensive lockdowns, quarantines, smart working and the closure of numerous recreational or personal care activities due to the COVID-19 pandemic have not only heavily changed the habits and behaviors of all of us, but have also had consequences on the release of some types of pollutants. The aim of this study was to evaluate the possible changes due to the indirect effects of the pandemic in the contamination of plastic mixtures sampled in 9 sites of the main watercourses of the metropolitan city of Milan (N. Italy), which is one of the major industrialized and urbanized areas in Italy. To achieve this goal, we carried out two sampling campaigns, the first one carried out in November 2019, before the arrival of the SARS-CoV-2 virus in Italy, the second in November 2020, during a severe regional lockdown that coincided with other restrictions imposed at the national level.The main results showed a difference in contamination of plastics between the two samplings, not so much due to a quantitative variation, but certainly qualitative. We obtained non-homogeneous data with respect to changes in the number of plastics sampled in the different waterbodies, while it was evident that the plastics' contamination has shifted from a primary and industrial origin to one due to a secondary origin of the sampled plastics, linked especially to the fragmentation of common use objects, or deriving from synthetic garments.

Human Mobility-based Individual-level Epidemic Simulation Platform

COVID-19 has spread worldwide, and over 140 million people have been confirmed infected, over 3 million people have died, and the numbers are still increasing dramatically. The consensus has been reached by scientists that COVID-19 can be transmitted in an airborne way, and human-to-human transmission is the primary cause of the fast spread of COVID-19. Thus, mobility should be restricted to control the epidemic, and many governments worldwide have succeeded in curbing the spread by means of control policies like city lockdowns. Against this background, we propose a novel fine-grained transmission model based on real-world human mobility data and develop a platform that helps the researcher or governors to explore the possibility of future development of the epidemic spreading and simulate the outcomes of human mobility and the epidemic state under different epidemic control policies. The proposed platform can also support users to determine potential contacts, discover regions with high infectious risks, and assess the individual infectious risk. The multi-functional platform aims at helping the users to evaluate the effectiveness of a regional lockdown policy and facilitate the process of screening and more accurately targeting the potential virus carriers.

Comparing air quality during nationwide and regional lockdown in Mumbai Metropolitan City of India

The second wave of COVID-19 triggered crises in India and resulted in a regional scale lockdown (March 2021), exempting specific economic sectors from economic misery. A national lockdown was announced during the first wave of this pandemic (March, 2020), resulting in a dramatic improvement in air quality. The present study explored whether the regional lockdown has an equal influence on air quality in various urban morphological units as the national lockdown. Results show that the regional lockdown in 2021 improved air quality by 32% more than the national lockdown in 2020. The rate of air quality improved between pre-lockdown and during a nationwide lockdown was 33%, 41% and 15% in industrial, commercial, and residential zones, respectively, but 53%, 46% and 43% during the regional lockdown. Because of the regional lockdown, air quality has improved at a quicker pace.

Market reaction to the Covid-19 pandemic: Events study at stocks listed on LQ45 index

This study aims to examine the market reaction to the Covid-19 pandemic using stocks listed on the LQ45 Index, by using the event study method to calculate and analyze the difference in Average Abnormal Return (AAR) and Trading Volume Trading (TVA) during the Covid-19 pandemic that occurred in Indonesia. The population for the study is companies listed on the LQ45 Index with a sample of 41 companies taken by purposive sampling technique. Statistical analysis was conducted by using events study with paired sample t-test in determining the abnormal return difference test for each event. The first finding was that the LQ45 stock market reacted positively since the confirmation of the Covid-19 outbreak in Wuhan, China, as investors did not consider this information bad news. Second, LQ45 shares have shown a decline since the first confirmed Covid-19 patients in Indonesia. Third, the announcement of a pandemic by the World Health Organization (WHO) continued until the Jakarta regional lockdown in April 2020 made LQ45 respond negatively. The market began to respond positively after the first vaccination in Indonesia in January 2021. Overall, the results show that the LQ45 stock market has responded quickly to the Covid-19 pandemic from the start events and responses vary over time depending on events during the pandemic. Investors tend to be quick to respond to any event so that stock movements are very difficult to project. This research concludes that the negative impact occurred on the stock market in Indonesia could be attributed to the Covid-19 pandemic.

Household visitation during the COVID-19 pandemic

The COVID-19 pandemic has posed novel risks related to the indoor mixing of individuals from different households and challenged policymakers to adequately regulate this behaviour. While in many cases household visits are necessary for the purpose of social care, they have been linked to broadening community transmission of the virus. In this study we propose a novel, privacy-preserving framework for the measurement of household visitation at national and regional scales, making use of passively collected mobility data. We implement this approach in England from January 2020 to May 2021. The measures expose significant spatial and temporal variation in household visitation patterns, impacted by both national and regional lockdown policies, and the rollout of the vaccination programme. The findings point to complex social processes unfolding differently over space and time, likely informed by variations in policy adherence, vaccine relaxation, and regional interventions.