The effects of air transport mobility and global connectivity on viral transmission: Lessons learned from Covid-19 and its variants

Paving initial forecasting COVID-19 spread capabilities by nonexperts: A case study

Objective

The COVID-19 outbreak compelled countries to take swift actions across various domains amidst substantial uncertainties. In Israel, significant COVID-19-related efforts were assigned to the Israeli Home Front Command (HFC). HFC faced the challenge of anticipating adequate resources to efficiently and timely manage its numerous assignments despite the absence of a COVID-19 spread forecast. This paper describes the initiative of a group of motivated, though nonexpert, people to provide the needed COVID-19 rate of spread of the epidemic forecasts.

Methods

To address this challenge, the Planning Chamber, reporting to the HFC Medical Commander, undertook the task of mapping HFC healthcare challenges and resource requirements. The nonexpert team continuously collected public COVID-19-related data published by the Israeli Ministry of Health (MoH) of verified cases, light cases, mild cases, serious condition cases, life-support cases, and deaths, and despite lacking expertise in statistics and healthcare and having no sophisticated statistical packages, generated forecasts using Microsoft® Excel.

Results

The analysis methods and applications successfully demonstrated the desired outcome of the lockdown by showing a transition from exponential to polynomial growth in the spread of the virus. These forecasting activities enabled decision-makers to manage resources effectively, supporting the HFC's operations during the pandemic.

Conclusions

Nonexpert forecasting may become a necessity and be beneficial, and similar analysis efforts can be easily replicated in future events. However, they are inherently short-lived and should persist only until knowledge centers can bridge the expertise gap. It is crucial to identify major events, such as lockdowns, during forecasting due to their potential impact on spread rates. Despite the expertise gap, the Planning Chamber's approach provided valuable resource management insights for HFC's COVID-19 response.

Early response to COVID-19 in Brazil: The impact of a targeted approach to suspected cases and on epidemiological surveillance efforts

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entered Brazil before travel restrictions and border closures were imposed. This study reports the characteristics of suspected and confirmed coronavirus disease 2019 (COVID-19) cases among symptomatic international travelers in Brazil and their contacts.

Methods

The REDCap platform developed by the Brazilian Ministry of Health was analyzed to identify and investigate suspected cases of COVID-19 recorded during the period January 1 to March 20, 2020. The impact of Brazil's targeted approach to suspected cases from specific countries on epidemiological surveillance efforts during the early stages of the COVID-19 pandemic were analyzed.

Results

Based on molecular RT-PCR tests, there were 217 (4.2%) confirmed, 1030 (20.1%) unconfirmed, 722 (14.1%) suspected, and 3157 (61.6%) non-investigated cases among travelers returning from countries included on the alert list for surveillance, as defined by the Ministry of Health. Among the 3372 travelers who went to countries not included on the alert list, there were 66 (2.0%) confirmed, 845 (25.3%) unconfirmed, 521 (15.6%) suspected, and 1914 (57.2%) non-investigated cases. A comparison of the characteristics of confirmed cases returning from alert and non-alert countries did not reveal a statistically significant difference in symptoms. Almost half of the hospitalized travelers with known travel dates and hospitalization status (53.6%) were inbound from countries not included on the alert list, and RT-PCR tests were reported for only 30.5%.

Conclusions

Policies adopted at entry points to contain the introduction of SARS-CoV-2 in Brazil were not ideal. An analysis of the early response shows that surveillance of travelers, including testing strategies, data standards, and reporting systems, was insufficient.

On the contagion leakage via incoming flights during China's aviation policies in the fight against COVID-19

For nearly three years with the COVID-19 pandemic, China has implemented a set of strict policies to control the flux of potential virus carriers in cross-border flights: The so-called Circuit Breaker mechanism. In this study, we review the evolution of this mechanism - a rather unique experiment in the global aviation system - from a data-driven perspective. Specifically, we perform an investigation on the extent of violations and their potential drivers. In total, 183 events are analyzed covering the period from epidemic outbreak in early 2020 to December 2021. In addition to describing the spatial extent and temporal evolution, we develop a regression model which helps us to better understand the universal patterns. By dissecting an under-investigated phenomenon, we believe that our study contributes to the rich literature on aviation and COVID-19, not only in the specific context of China, but also by assessing some of the challenges and potential of containing a global health threat using strict aviation policies.

Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility

The unprecedented COVID-19 outbreak has significantly influenced our daily life, and COVID-19's spread is inevitably associated with human mobility. Given the pandemic's severity and extent of spread, a timely and comprehensive synthesis of the current state of research is needed to understand the pandemic's impact on human mobility and corresponding government measures. This study examined the relevant literature published to the present (March 2023), identified research trends, and conducted a systematic review of evidence regarding transport's response to COVID-19. We identified key research agendas and synthesized the results, examining: (1) mobility changes by transport modes analyzed regardless of government policy implementation, using empirical data and survey data; (2) the effect of diverse government interventions to reduce mobility and limit COVID-19 spread, and controversial issues on travel restriction policy effects; and (3) future research issues. The findings showed a strong relationship between the pandemic and mobility, with significant impacts on decreased overall mobility, a remarkable drop in transit ridership, changes in travel behavior, and improved traffic safety. Government implemented various non-pharmaceutical countermeasures, such as city lockdowns, travel restrictions, and social distancing. Many studies showed such interventions were effective. However, some researchers reported inconsistent outcomes. This review provides urban and transport planners with valuable insights to facilitate better preparation for future health emergencies that affect transportation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11116-023-10392-2.

Investigating the relationships between concentrated disadvantage, place connectivity, and COVID-19 fatality in the United States over time

BACKGROUND

Concentrated disadvantaged areas have been disproportionately affected by COVID-19 outbreak in the United States (US). Meanwhile, highly connected areas may contribute to higher human movement, leading to higher COVID-19 cases and deaths. This study examined the associations between concentrated disadvantage, place connectivity, and COVID-19 fatality in the US over time.

METHODS

Concentrated disadvantage was assessed based on the spatial concentration of residents with low socioeconomic status. Place connectivity was defined as the normalized number of shared Twitter users between the county and all other counties in the contiguous US in a year (Y = 2019). COVID-19 fatality was measured as the cumulative COVID-19 deaths divided by the cumulative COVID-19 cases. Using county-level (N = 3,091) COVID-19 fatality over four time periods (up to October 31, 2021), we performed mixed-effect negative binomial regressions to examine the association between concentrated disadvantage, place connectivity, and COVID-19 fatality, considering potential state-level variations. The moderation effects of county-level place connectivity and concentrated disadvantage were analyzed. Spatially lagged variables of COVID-19 fatality were added to the models to control for the effect of spatial autocorrelations in COVID-19 fatality.

RESULTS

Concentrated disadvantage was significantly associated with an increased COVID-19 fatality in four time periods (p < 0.01). More importantly, moderation analysis suggested that place connectivity significantly exacerbated the harmful effect of concentrated disadvantage on COVID-19 fatality in three periods (p < 0.01), and this significant moderation effect increased over time. The moderation effects were also significant when using place connectivity data from the previous year.

CONCLUSIONS

Populations living in counties with both high concentrated disadvantage and high place connectivity may be at risk of a higher COVID-19 fatality. Greater COVID-19 fatality that occurs in concentrated disadvantaged counties may be partially due to higher human movement through place connectivity. In response to COVID-19 and other future infectious disease outbreaks, policymakers are encouraged to take advantage of historical disadvantage and place connectivity data in epidemic monitoring and surveillance of the disadvantaged areas that are highly connected, as well as targeting vulnerable populations and communities for additional intervention.