The emergence of Covid-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with highly disaggregated spatial and temporal units of analysis, are a priority in this sense. Spatio-temporal models provide a geographically detailed and temporally updated overview of the current state of the pandemics, making public health interventions to be more effective. Moreover, the use of spatio-temporal disease mapping models in the new Covid-19 epidemic context, facilitates estimating newly demanded epidemiological indicators, such as the instantaneous reproduction number (R_t), even for small areas. This, in turn, allows to adapt traditional disease mapping models to these new circumstancies and make their results more useful in this particular context.
In this paper we propose a new spatio-temporal disease mapping model, particularly suited to Covid-19 surveillance. As an additional result, we derive instantaneous reproduction number estimates for small areas, enabling monitoring this parameter with a high spatial disaggregation. We illustrate the use of our proposal with the separate study of the disease pandemics in two Spanish regions. As a result, we illustrate how touristic flows could haved shaped the spatial distribution of the disease. In these real studies, we also propose new surveillance tools that can be used by regional public health services to make a more efficient use of their resources.
COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares observed with expected deaths based on the assumption that the pandemic did not occur. Expected deaths had the pandemic not occurred depend on population trends, temperature, and spatio-temporal patterns. In addition to this, high geographical resolution is required to examine within country trends and the effectiveness of the different public health policies. In this tutorial, we propose a framework using R …
Accurate forecasting of the U.K. gross value added (GVA) is fundamental for measuring the growth of the U.K. economy. A common nonstationarity in GVA data, such as the ABML series, is its increase in variance over time due to inflation. Transformed or inflation-adjusted series can still be challenging for classical stationarity-assuming forecasters. We adopt a different approach that works directly with the GVA series by advancing recent forecasting methods for locally stationary time series. Our approach results in more accurate and reliable forecasts, and continues to work well even when the…
The COVID-19 pandemic has been influencing travel behaviour in many urban areas around the world since the beginning of 2020. As a consequence, bike-sharing schemes have been affected partly due to the change in travel demand and behaviour as well as a shift from public transit. This study estimates the varying effect of the COVID-19 pandemic on the London bike-sharing system (Santander Cycles) over the period March-December 2020. We employed a Bayesian second-order random walk time-series model to account for temporal correlation in the data. We compared the observed number of cycle hires and…
We present an extension of the Li and Lee model to quantify mortality in five European countries during the COVID-19 pandemic. The first two factors are used to model the pre-COVID mortality, with the first layer modelling the common trend and the second layer the country-specific deviation from the common trend. We add a third layer to capture the country-specific impact of COVID-19 in 2020 and 2021 in excess of the pre-COVID trend. We use weekly mortality data from the Short Term Mortality Fluctuations Database to calibrate this third factor, and we use a more granular dataset for deaths in …
The COVID-19 pandemic triggered a question of how to measure and evaluate adequacy of the applied restrictions. Available studies propose various methods mainly grouped to statistical and machine learning techniques. The current paper joins this line of research by introducing a simple-yet-accurate linear regression model which eliminates effects of weekly cycle, available daylight, temperature, and wind from the electricity consumption data. The model is validated using real data and enables the qualitative analysis of economical impact.
COVID19 has impacted Indian engineering institutions (EIs) enormously. It has tightened its knot around EIs that forced their previous half shut shades completely down to prevent the risk of spreading COVID19. In such a situation, fetching new enrollments on EI campuses is a difficult and challenging task, as students behavior and family preferences have changed drastically due to mental stress and emotions attached to them. Consequently, it becomes a prerequisite to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic to make it normal for new enroll…
Since the outbreak of COVID-19, it has rapidly evolved into a sudden and major public health emergency globally. With the variants of COVID-19, the difficulty of pandemic control continues to increase, which has brought significant costs to the society. The existing pandemic control zoning method ignores the impact on residents'lives. In this study, we propose a refined and low-cost pandemic control method by scientifically delineating zoning areas. First, a spatial interaction network is built up based on the multimodal transport travel data in Nanjing, China, and an improved Leiden community…
While there is an emergence of research investigating the educational impacts of the COVID-19 pandemic, empirical studies assessing teacher mental health throughout the pandemic have been scarce. Using a large national dataset, the current study first compared mental health outcomes during the pandemic between pK-12 teachers and professionals in other occupations. Further, we compared the prevalence of mental health outcomes between in-person and remote teachers (n = 131,154). Findings indicated teachers reported greater mental health concerns than those in other professions, and that remote t…
This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in two contrasting US states during 2020-2021. A variety of models are evaluated at the county level for goodness-of-fit and an assessment of confounding predictors is also made. It is found that models with three deprivation predictors and neighborhood effects are important. In addition the work index from Google mobility was also found to provide increased explanation of the transmission dynamic.
Detecting changes in COVID-19 disease transmission over time is a key indicator of epidemic growth.Near real-time monitoring of the pandemic growth is crucial for policy makers and public health officials who need to make informed decisions about whether to enforce lockdowns or allow certain activities. The effective reproduction number Rt is the standard index used in many countries for this goal. However, it is known that due to the delays between infection and case registration, its use for decision making is somewhat limited. In this paper a near real-time COVINDEX is proposed for monitori…
When testing for a disease such as COVID-19, the standard method is individual testing: we take a sample from each individual and test these samples separately. An alternative is pooled testing (or "group testing"), where samples are mixed together in different pools, and those pooled samples are tested. When the prevalence of the disease is low and the accuracy of the test is fairly high, pooled testing strategies can be more efficient than individual testing. In this chapter, we discuss the mathematics of pooled testing and its uses during pandemics, in particular the COVID-19 pandemic. We a…
Very recently the new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified and the coronavirus disease 2019 (COVID-19) declared a pandemic by the World Health Organization. The pandemic has a number of consequences for the ongoing clinical trials in non-COVID-19 conditions. Motivated by four currently ongoing clinical trials in a variety of disease areas we illustrate the challenges faced by the pandemic and sketch out possible solutions including adaptive designs. Guidance is provided on (i) where blinded adaptations can help; (ii) how to achieve type I error r…
The current outbreak of COVID-19 has called renewed attention to the need for sound statistical analysis for monitoring mortality patterns and trends over time. Excess mortality has been suggested as the most appropriate indicator to measure the overall burden of the pandemic on mortality. As such, excess mortality has received considerable interest during the first months of the COVID-19 pandemic. Previous approaches to estimate excess mortality are somewhat limited, as they do not include sufficiently long-term trends, correlations among different demographic and geographic groups, and the a…
Introduction: The aim of our retrospective study was to quantify the impact of Covid-19 on the temporal distribution of Emergency Medical Services (EMS) demand in Travis County, Austin, Texas and propose a robust model to forecast Covid-19 EMS incidents. Methods: We analyzed the temporal distribution of EMS calls in the Austin-Travis County area between January 1st, 2019, and December 31st, 2020. Change point detection was performed to identify critical dates marking changes in EMS call distributions, and time series regression was applied for forecasting Covid-19 EMS incidents. Results: Two c…
The Republic of Cyprus is a small island in the southeast of Europe and member of the European Union. The first wave of COVID-19 in Cyprus started in early March, 2020 (imported cases) and peaked in late March-early April. The health authorities responded rapidly and rigorously to the COVID-19 pandemic by scaling-up testing, increasing efforts to trace and isolate contacts of cases, and implementing measures such as closures of educational institutions, and travel and movement restrictions. The pandemic was also a unique opportunity that brought together experts from various disciplines includ…
The academic, socioemotional, and health impacts of school policies throughout the COVID-19 pandemic have been a source of many important questions that require accurate information about the extent of onsite schooling that has been occurring throughout the pandemic. This paper investigates school operational status data sources during the COVID-19 pandemic, comparing self-report data collected nationally on the household level through a Facebook-based survey with data collected at district and county levels throughout the country. The percentage of households reporting in-person instruction w…
Coronavirus disease 2019 (COVID-19) is associated with a very high number of casualties in the general population. Assessing the exact magnitude of this number is a non-trivial problem, as relying only on officially reported COVID-19 associated fatalities runs the risk of incurring in several kinds of biases. One of the ways to approach the issue is to compare overall mortality during the pandemic with expected mortality computed using the observed mortality figures of previous years. In this paper, we build on existing methodology and propose two ways to compute expected as well as excess mor…
During the Covid-19 pandemic, most governments across the world imposed policies like lock-down of public spaces and restrictions on people's movements to minimize the spread of the virus through physical contact. However, such policies have grave social and economic costs, and so it is important to pre-assess their impacts. In this work we aim to visualize the dynamics of the pandemic in a city under different intervention policies, by simulating the behavior of the residents. We develop a very detailed agent-based model for a city, including its residents, physical and social spaces like hom…
COVID-19 pandemic has shaken the roots of healthcare facilities worldwide, with the US being one of the most affected countries irrespective of being a superpower. Along with the current pandemic, COVID-19 can cause a secondary crisis of mental health pandemic if left unignored. Various studies from past epidemics, financial turmoil and pandemic, especially SARS and MERS, have shown a steep increase in mental and psychological issues like depression, low quality of life, self-harm and suicidal tendencies among general populations. The most venerable being the individuals infected and cured due…
Official counts of COVID-19 deaths have been criticized for potentially including people who did not die of COVID-19 but merely died with COVID-19. I address that critique by fitting a generalized additive model to weekly counts of all deaths registered in England and Wales during the 2010s. The model produces baseline rates of death registrations expected without the COVID-19 pandemic, and comparing those baselines to recent counts of registered deaths exposes the emergence of excess deaths late in March 2020. By April's end, England and Wales registered 45,300 $\pm$ 3200 excess deaths of adu…
College of Computing, Georgia Institute of Technology（佐治亚理工学院计算学院）；Department of Computer Science, Virginia Tech（弗吉尼亚理工大学计算机系）；Department of Computer Science, University of Iowa（爱荷华大学计算机系）
Forecasting influenza in a timely manner aids health organizations and policymakers in adequate preparation and decision making. However, effective influenza forecasting still remains a challenge despite increasing research interest. It is even more challenging amidst the COVID pandemic, when the influenza-like illness (ILI) counts are affected by various factors such as symptomatic similarities with COVID-19 and shift in healthcare seeking patterns of the general population. Under the current pandemic, historical influenza models carry valuable expertise about the disease dynamics but face di…
Monitoring the evolution of the Covid19 pandemic constitutes a critical step in sanitary policy design. Yet, the assessment of the pandemic intensity within the pandemic period remains a challenging task because of the limited quality of data made available by public health authorities (missing data, outliers and pseudoseasonalities, notably), that calls for cumbersome and ad-hoc preprocessing (denoising) prior to estimation. Recently, the estimation of the reproduction number, a measure of the pandemic intensity, was formulated as an inverse problem, combining data-model fidelity and space-ti…
The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we characterize collective physical distancing -- mobility reductions, minimization of contacts, shortening of contact duration -- in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users…
The COVID-19 pandemic has drastically impacted people's travel behaviour and out-of-home activity participation. While countermeasures are being eased with increasing vaccination rates, the demand for public transport remains uncertain. To investigate user preferences to travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N=961). We analysed the collected data using multinomial and mixed logit models. Our analysis provides insights into the sensitivity of the demand for the London Underground with respect to travel attributes …
A mathematical model for the COVID-19 pandemic spread, which integrates age-structured Susceptible-Exposed-Infected-Recovered-Deceased dynamics with real mobile phone data accounting for the population mobility, is presented. The dynamical model adjustment is performed via Approximate Bayesian Computation. Optimal lockdown and exit strategies are determined based on nonlinear model predictive control, constrained to public-health and socio-economic factors. Through an extensive computational validation of the methodology, it is shown that it is possible to compute robust exit strategies with r…
