scholarly journals Integrating psychosocial variables and societal diversity in epidemic models for predicting COVID-19 transmission dynamics

2020 ◽  
Author(s):  
Viktor Jirsa ◽  
Spase Petkoski ◽  
Huifang Wang ◽  
Marmaduke Woodman ◽  
Jan Fousek ◽  
...  
Keyword(s):  
Human Mobility ◽  
Disease Spread ◽  
Vulnerable Groups ◽  
Psychosocial Variables ◽  
Cross Sectional ◽  
Societal Factors ◽  
Spread Model ◽  
Careful Handling ◽  
Diverse Groups ◽  
The Impact

During the current COVID-19 pandemic, governments must make decisions based on a variety of information including estimations of infection spread, health care capacity, economic and psychosocial considerations. The disparate validity of current short-term forecasts of these factors is a major challenge to governments. By causally linking an established epidemiological spread model with dynamically evolving psychosocial variables, using Bayesian inference we estimate the strength and direction of these interactions for German and Danish data of disease spread, human mobility, and psychosocial factors based on the serial cross-sectional COVID-19 Snapshot Monitoring (COSMO; N = 16,981). We demonstrate that the strength of cumulative influence of psychosocial variables on infection rates is of a similar magnitude as the influence of physical distancing. We further show that the efficacy of political interventions to contain the disease strongly depends on societal diversity, in particular group-specific sensitivity to affective risk perception. As a consequence, the model may assist in quantifying the effect and timing of interventions, forecasting future scenarios, and differentiating the impact on diverse groups as a function of their societal organization. Importantly, the careful handling of societal factors, including support to the more vulnerable groups, adds another direct instrument to the battery of political interventions fighting epidemic spread.

scholarly journals A Linear Dynamical Perspective on Epidemiology: Interplay Between Early COVID-19 Outbreak and Human Mobility

2021 ◽  
Author(s):  
Shakib Mustavee ◽  
Shaurya Agarwal ◽  
Suddhasattwa Das ◽  
Chinwendu Enyioha
Keyword(s):  
Human Mobility ◽  
Dynamic Mode Decomposition ◽  
Disease Spread ◽  
Dynamic Mode ◽  
Control Input ◽  
Mobility Patterns ◽  
Spread Model ◽  
Spread Dynamics ◽  
The Impact ◽  
Locally Linear

Abstract This paper investigates the impact of human activity and mobility (HAM) in the spreading dynamics of an epidemic. Specifically, it explores the interconnections between HAM and its effect on the early spread of the COVID-19 virus. During the early stages of the pandemic, effective reproduction numbers exhibited a high correlation with human mobility patterns, leading to a hypothesis that the HAM system can be studied as a coupled system with disease spread dynamics. This study applies the generalized Koopman framework with control inputs to determine the nonlinear disease spread dynamics and the input-output characteristics as a locally linear controlled dynamical system. The approach solely relies on the snapshots of spatiotemporal data and does not require any knowledge of the system’s physical laws. We exploit the Koopman operator framework by utilizing the Hankel Dynamic Mode Decomposition with Control (HDMDc) algorithm to obtain a linear disease spread model incorporating human mobility as a control input. The study demonstrated that the proposed methodology could capture the impact of local mobility on the early dynamics of the ongoing global pandemic. The obtained locally linear model can accurately forecast the number of new infections for various prediction windows ranging from two to four weeks. The study corroborates a leader-follower relationship between mobility and disease spread dynam-

scholarly journals Impact of temperature and relative humidity on the transmission of COVID-19: a modelling study in China and the United States

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e043863
Author(s):  
Jingyuan Wang ◽  
Ke Tang ◽  
Kai Feng ◽  
Xin Lin ◽  
Weifeng Lv ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Human Mobility ◽  
The United States ◽  
Reproductive Number ◽  
Cross Sectional ◽  
The Usa ◽  
Higher Temperature ◽  
Potential Impact ◽  
The Impact

ObjectivesWe aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status.DesignA retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted.SettingWe use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties.ParticipantsA total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers.Primary outcome measuresRegression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).ResultsStatistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the USA.ConclusionsHigher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (−0.0395 to −0.0125)) in China and by 0.020 (95% CI (−0.0311 to −0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (−0.0108 to −0.0045)) in China and by 0.0080 (95% CI (−0.0150 to −0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

scholarly journals Unravelling the impact of COVID-19 on mental health: A scoping review on traumatogenic events using the phases of response to disaster model

2021 ◽  
pp. 218-236
Author(s):  
den Cruyce Nele Van
Keyword(s):  
Mental Health ◽  
Scoping Review ◽  
Disaster Response ◽  
Mental Health Problems ◽  
Economic Status ◽  
Psychological Needs ◽  
Vulnerable Groups ◽  
Cross Sectional ◽  
The Impact ◽  
Over Time

Background: Disease outbreaks such as the COVID-19 pandemic give rise to high levels of psychological distress in people worldwide. Since this is the first pandemic of its kind, the best available evidence is needed on what psychological needs could be expected during and after the pandemic. Objectives: In this scoping review existing research on traumatogenic events is examined in order to identify the potential impact on mental health of the COVID pandemic. The research findings are organized using the the phases of disaster response model. Results: A total of 34 longitudinal studies, 2 studies with multiple waves of data collection and 92 cross-sectional studies met the inclusion criteria. The studies included in this scoping review could be classified as: 87 studies on COVID-19, 2 on SARS, 19 on wars, 19 on terrorist attacks and 1 on a nuclear accident. Results indicate that stress, anxiety, depressive symptoms, insomnia, denial, anger, grief and fear can be anticipated as common reactions. The longer a pandemic continues, the higher the psychological strain is expected to be. Conclusions: The phases of response to disaster model offers a valid frame to unravel the impact of the pandemic on mental health over time. Specific attention must be given to vulnerable groups, whereby specific risk factors include age, gender, pre-existing mental health problems, healthcare profession, migration background, isolation and low socio economic status. However, these may change over time, and a delayed manifestation of psychosocial problems needs to be considered too. Mental health governance is, therefore, warranted throughout and even up to 6 months after the pandemic.

scholarly journals Lockdown related travel behavior undermines the containment of SARS-CoV-2

2020 ◽  
Author(s):  
Nishant Kishore ◽  
Rebecca Kahn ◽  
Pamela P. Martinez ◽  
Pablo M. De Salazar ◽  
Ayesha S. Mahmud ◽  
...  
Keyword(s):  
Rural Areas ◽  
Travel Behavior ◽  
Human Mobility ◽  
Unintended Consequences ◽  
Disease Spread ◽  
Mobility Patterns ◽  
Long Distance ◽  
Mobility Data ◽  
Travel Restrictions ◽  
The Impact

ABSTRACTIn response to the SARS-CoV-2 pandemic, unprecedented policies of travel restrictions and stay-at-home orders were enacted around the world. Ultimately, the public’s response to announcements of lockdowns - defined here as restrictions on both local movement or long distance travel - will determine how effective these kinds of interventions are. Here, we measure the impact of the announcement and implementation of lockdowns on human mobility patterns by analyzing aggregated mobility data from mobile phones. We find that following the announcement of lockdowns, both local and long distance movement increased. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, we developed a simple agent-based spatial model. We find that travel surges following announcements of lockdowns can increase seeding of the epidemic in rural areas, undermining the goal of the lockdown of preventing disease spread. Appropriate messaging surrounding the announcement of lockdowns and measures to decrease unnecessary travel are important for preventing these unintended consequences of lockdowns.

scholarly journals Impact of the Coronavirus Pandemic (COVID-19) Lockdown on Mental Health and Well-Being in the United Arab Emirates

2021 ◽  
Vol 12 ◽  
Author(s):  
Leila Cheikh Ismail ◽  
Maysm N. Mohamad ◽  
Mo'ath F. Bataineh ◽  
Abir Ajab ◽  
Amina M. Al-Marzouqi ◽  
...  
Keyword(s):  
Mental Health ◽  
United Arab Emirates ◽  
Psychological Impact ◽  
Well Being ◽  
Vulnerable Groups ◽  
University Graduates ◽  
Online Questionnaire ◽  
Cross Sectional ◽  
Event Scale ◽  
The Impact

United Arab Emirates (UAE) has taken unprecedented precautionary measures including complete lockdowns against COVID-19 to control its spread and ensure the well-being of individuals. This study investigated the impact of COVID-19 and societal lockdown measures on the mental health of adults in the UAE. A cross-sectional study was conducted using an English and Arabic online questionnaire between May and June 2020. The psychological impact was assessed by the Impact of Event Scale-Revised (IES-R), and the social and family support impact was evaluated using questions from the Perceived Support Scale (PSS). A total of 4,426 participants (3,325 females and 1,101 males) completed the questionnaire. The mean IES-R score was 28.0 ± 14.6, reflecting a mild stressful impact with 27.3% reporting severe psychological impact. Over 36% reported increased stress from work, home and financial matters. Also, 43–63% of the participants felt horrified, apprehensive or helpless due to COVID-19. Females, younger participants, part-timers, and college or University graduates were more likely to have a high IES-R score (p < 0.05). The majority of participants reported receiving increased support from family members, paying more attention to their mental health, and spending more time to rest and relax. The results of this study demonstrate the impact of the COVID-19 pandemic on mental health among the UAE residents and highlight the need to adopt culturally appropriate interventions for the general population and vulnerable groups, such as females and younger adults.

scholarly journals Epidemic Spreading in Urban Areas Using Agent-Based Transportation Models

2019 ◽  
Vol 11 (4) ◽  
pp. 92 ◽  
Author(s):  
Jürgen Hackl ◽  
Thibaut Dubernet
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Human Mobility ◽  
Urban Setting ◽  
Disease Spread ◽  
Model Parameters ◽  
Epidemic Spreading ◽  
Agent Based ◽  
Spread Model ◽  
Spread Dynamics

Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic.

INVESTIGATING THE ROLE OF WITHIN- AND BETWEEN-PATCH MOVEMENT IN A DYNAMIC MODEL OF DISEASE SPREAD

2020 ◽  
Vol 28 (04) ◽  
pp. 815-837
Author(s):  
KLOT PATANARAPEELERT
Keyword(s):  
Dynamic Model ◽  
Gravity Model ◽  
Transmission Rate ◽  
Human Mobility ◽  
Disease Spread ◽  
The Difference ◽  
Invasion Threshold ◽  
The Impact ◽  
Local Transmission

The impact of human mobility on the spreading of disease in a metapopulation is emphasized on interconnecting between patches, whereas the current volume of movement within the local population is usually neglected. Here, the role of internal commuters is taken into account by two means, a local transmission rate and the volume of internal commuters. Dynamic model of human mobility in the metapopulation with gravity coupling is presented. In conjunction with the disease spreading, the impact on invasion threshold and epidemic final size are analyzed. For two-patch model, we show that under fixing parameters in gravity model, the existence of invasion threshold depends on the difference of local transmission rates and the proportion of internal commuters between two patches. For a fully connected network with an identical transmission rate, the difference in patch final sizes is driven by patch distribution of internal commuters. By neglecting the effect of spatial variation in a simple core–satellite model, we show that the heterogeneity of internal commuters and gravity coupling induce a complex pattern of threshold, which depend mostly on the exponent in gravity model, and are responsible for the differences among local epidemic sizes.

scholarly journals Moderate to vigorous physical activity and sedentary behavior change in self-isolating adults during the COVID-19 pandemic in Brazil: A cross-sectional survey exploring correlates

2020 ◽  
Author(s):  
Felipe Schuch ◽  
Rugero Bulzing ◽  
Jacob Meyer ◽  
Guillermo Lopez-Sanchez ◽  
Igor Grabovac ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Online Survey ◽  
Vigorous Physical Activity ◽  
Self Report ◽  
Vulnerable Groups ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Previous Diagnosis ◽  
The Impact

Background: The self-distancing measures imposed major changes in daily life routine. This study aimed to (i) evaluate the changes (pre-versus during pandemic) in time spent in moderate to vigorous physical activity (MVPA) and sedentary behavior (SB) in selfisolating Brazilians during the COVID-19 pandemic, and (ii) to explore correlates of MVPA and SB. Methods: A cross-sectional self-report online survey, evaluating the time spent in MVPA and SB pre and during the COVID-19 pandemic. Sociodemographic, behavioral, clinical, variables, and time in self-isolation were also obtained. Changes in MVPA and SB and their correlates were explored using generalized estimating equations (GEE). Results: A total of 877 participants (72.7% women, 53.7% young adults [18-34 years]) were included. Overall, participants reported a 59.7% reduction (95%CI:35.6 to 82.2) in time spent on MVPA during the pandemic. Time spent in SB increased 42.0% (95%CI:31.7 to 52.5). Greater reductions in MVPA and/or increases in SB were seen in younger adults, those not married, those employed and those with a self-reported previous diagnosis of a mental disorder. Conclusions: People in self-isolation significantly reduced MVPA levels and increased SB. Public health strategies should be implemented during epidemic times to mitigate the impact of self-isolation on MVPA and SB, particularly in vulnerable groups.

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