Evolution and early government responses to COVID-19 in South America

González‐Bustamante, Bastián

doi:10.1016/j.worlddev.2020.105180

Cited by 72 publications

(53 citation statements)

References 24 publications

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“…The left column describes the main categories in this group of articles. Subcategory Country and references Effects on spreading Argentina, Bolivia, Brazil, Chile, Colombia, Paraguay, Peru, and Uruguay [309] ; Australia [310] Bangladesh [311] ; China [31] , [32] , [33] , [312] , [313] , [314] , [315] ; China, Germany, India, Italy, Singapore, South Korea, Spain, UK, USA [316] ; Italy [317] , [318] ; New Zealand [319] ; Puerto Rico [320] ; South Korea [321] ; Taiwan [322] ; USA [323] , [324] , [325] , [326] , [327] , [328] ; 44 countries [329] ; 53 countries [330] ; 56 countries [331] ; 142 countries [332] ; 149 countries [333] Effects on behaviors China [334] ; China, Italy [335] ; Denmark, Sweden [336] ; Germany [337] USA [338] , [339] , [340] , [341] ; 20 countries [342] ; 67 countries [343] Effects on medical practice Italy [344] ; Netherlands [345] ; UK [346] …”

Section: Quantifying the Effects On Npismentioning

confidence: 99%

“…These articles study the impact on the unfolding of the disease focusing on the measures adopted in a specific country [31] , [32] , [33] , [309] , [310] , [311] , [312] , [313] , [315] , [317] , [318] , [319] , [320] , [322] , [323] , [324] , [325] , [326] , [327] , proposing multi country analyses [316] , [329] , [330] , [331] , [332] , [333] , and characterizing the effects of NPIs on other diseases [314] , [321] , [328] .…”

Section: Quantifying the Effects On Npismentioning

confidence: 99%

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Non-pharmaceutical interventions during the COVID-19 pandemic: A review

2021

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Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travels bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 of authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

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Section: Quantifying the Effects On Npismentioning

confidence: 99%

Section: Quantifying the Effects On Npismentioning

confidence: 99%

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

2021

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“…We de ne the time-at-risk for all countries as the start of the sample period (i.e., 01 January 2020) [10] and estimate the following strati ed (semi-parametric) Cox proportional hazards model [37][38]51]:…”

Section: Empirical Strategymentioning

confidence: 99%

“…[10] This approach is also used by [36] and [51] when examining the adoption rate of domestic NPI policies. [38] de nes the beginning time-at-risk as the date of the rst con rmed COVID-19 case of the country, thus treating countries which implemented a policy before having the rst con rmed case as left censored observations.…”

Section: Empirical Strategymentioning

confidence: 99%

How Does Globalization Affect COVID-19 Responses?

Bickley

Chan

Skali

et al. 2020

Preprint

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Background: The ongoing COVID-19 pandemic has highlighted the vast differences in approaches to the control and containment of coronavirus across the world and has demonstrated the varied success of such approaches in minimizing the transmission of coronavirus. While previous studies have demonstrated high predictive power of incorporating air travel data and governmental policy responses in global disease transmission modelling, factors influencing the decision to implement travel and border restriction policies have attracted relatively less attention. This paper examines the role of globalization on the pace of adoption of international travel-related non-pharmaceutical interventions (NPIs) during the coronavirus pandemic. This study aims to offer advice on how to improve the global planning, preparation, and coordination of actions and policy responses during future infectious disease outbreaks with empirical evidence.Results: The results of our survival analysis suggest that more globalized countries, accounting for the country-specific timing of the virus outbreak and other factors, are quicker to adopt international travel restrictions policies. However, countries with high government effectiveness were more cautious in the implementation of travel restrictions if they are more globalized, particularly if through formal political and trade policy integration. This finding is supported by a placebo analysis on domestic NPIs, where such a relationship is absent. Additionally, we find that globalized countries with high state capacity are more likely to have higher numbers of confirmed cases by the time a first restriction policy measure was taken. Conclusions: The findings highlight the dynamic relationship between globalization and protectionism when governments respond to significant global events such as a public health crisis. We suggest that the observed caution of policy implementation by countries with high government efficiency and globalization is a by-product of commitment to existing trade agreements, a greater desire to ‘learn from others’ and also perhaps of ‘confidence’ in a government’s ability to deal with a pandemic through its health system and state capacity. Our results suggest further research is warranted to explore whether global infectious disease forecasting could be improved by including the globalization index and in particular, the de jure trade and political (sub)dimensions and de facto interpersonal and cultural (sub)dimensions of globalization. By acting as proxies for a countries’ likelihood and speed of implementation for international travel restriction policies, such measures may predict the likely time delays in disease emergence and transmission across national borders.

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“…Several socioeconomic, demographic, and political factors make control of the pandemic in Latin America particularly challenging [ 22 – 25 ]. Most countries in the region are now facing the stark social and economic costs imposed by large-scale non-pharmaceutical interventions while largely failing to control the epidemic's spread [ 13 , 24 , 26 ]. Despite these unique conditions, the region has received relatively little attention from researchers globally [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Transmission dynamics and control of COVID-19 in Chile, March-October, 2020

et al. 2021

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Since the detection of the first case of COVID-19 in Chile on March 3rd, 2020, a total of 513,188 cases, including ~14,302 deaths have been reported in Chile as of November 2nd, 2020. Here, we estimate the reproduction number throughout the epidemic in Chile and study the effectiveness of control interventions especially the effectiveness of lockdowns by conducting short-term forecasts based on the early transmission dynamics of COVID-19. Chile’s incidence curve displays early sub-exponential growth dynamics with the deceleration of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number, R, estimated at 1.8 (95% CI: 1.6, 1.9). Our findings indicate that the control measures at the start of the epidemic significantly slowed down the spread of the virus. However, the relaxation of restrictions and spread of the virus in low-income neighborhoods in May led to a new surge of infections, followed by the reimposition of lockdowns in Greater Santiago and other municipalities. These measures have decelerated the virus spread with R estimated at ~0.96 (95% CI: 0.95, 0.98) as of November 2nd, 2020. The early sub-exponential growth trend (p ~0.8) of the COVID-19 epidemic transformed into a linear growth trend (p ~0.5) as of July 7th, 2020, after the reimposition of lockdowns. While the broad scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing and active case detection and isolation efforts to maintain the epidemic under control.

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Evolution and early government responses to COVID-19 in South America

Cited by 72 publications

References 24 publications

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

How Does Globalization Affect COVID-19 Responses?

Transmission dynamics and control of COVID-19 in Chile, March-October, 2020

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