Signatures of the Venezuelan Humanitarian Crisis in the First Wave of COVID-19: Fuel Shortages and Border Migration

Testing and isolation have been crucial for controlling the COVID-19 pandemic. Venezuela has one of the weakest testing infrastructures in Latin America and the low number of reported cases in the country has been attributed to substantial underreporting. However, the Venezuelan epidemic seems to have lagged behind other countries in the region, with most cases occurring within the capital region and four border states. Here, we describe the spatial epidemiology of COVID-19 in Venezuela and its relation to the population mobility, migration patterns, non-pharmaceutical interventions and fuel availability that impact population movement. Using a metapopulation model of SARS-CoV-2 transmission dynamics, we explore how movement patterns could have driven the observed distribution of cases. Low within-country connectivity most likely delayed the onset of the epidemic in most states, except for those bordering Colombia and Brazil, where high immigration seeded outbreaks. NPIs slowed early epidemic growth and subsequent fuel shortages appeared to be responsible for limiting the spread of COVID-19 across the country.

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Signatures of the Venezuelan Humanitarian Crisis in the First Wave of COVID-19: Fuel Shortages and Border Migration

10.20944/preprints202106.0044.v1 ◽

2021 ◽

Author(s):

Margarita Lampo ◽

Juan Vicente Hernández-Villena ◽

Jaime Cascante ◽

María Fernanda Vicenti-González ◽

David A. Forero-Peña ◽

...

Keyword(s):

Latin America ◽

Spatial Epidemiology ◽

Movement Patterns ◽

Population Mobility ◽

Metapopulation Model ◽

Humanitarian Crisis ◽

Migration Patterns ◽

Capital Region ◽

Border States ◽

Pharmaceutical Interventions

Testing and isolation have been crucial for controlling the COVID-19 pandemic. Venezuela has one of the weakest testing infrastructures in Latin America and the low number of reported cases in the country has been attributed to substantial underreporting. However, the Venezuelan epidemic seems to have lagged behind other countries in the region, with most cases occurring within the capital region and four border states. Here, we describe the spatial epidemiology of COVID-19 in Venezuela and its relation to population mobility, migration patterns, non-pharmaceutical interventions and fuel availability. Using an SEI metapopulation model, we explore how movement patterns could have driven the observed distribution of cases. Low within-country connectivity most likely delayed the epidemic in most states, except for those bordering Colombia and Brazil where high immigration seeded outbreaks. NPIs slowed early epidemic growth and subsequent fuel shortages appeared to be responsible for limiting the spread of COVID-19 across the country.

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Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study

BMJ Open ◽

10.1136/bmjopen-2020-047227 ◽

2021 ◽

Vol 11 (9) ◽

pp. e047227

Author(s):

Xiaoming Cui ◽

Lin Zhao ◽

Yuhao Zhou ◽

Xin Lin ◽

Runze Ye ◽

...

Keyword(s):

Close Contact ◽

Transmission Dynamics ◽

Contact Tracing ◽

Population Mobility ◽

Wholesale Market ◽

The People ◽

Spatiotemporal Analyses ◽

Epidemiological Characteristics ◽

Pharmaceutical Interventions ◽

Modelling Study

ObjectiveTo evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.DesignDescriptive and modelling study based on surveillance data of COVID-19 in Beijing.SettingOutbreak in Beijing.ParticipantsThe database included 335 confirmed cases of COVID-19.MethodsTo conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.ResultsWe found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.ConclusionsThe non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.

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Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Nature Communications ◽

10.1038/s41467-021-23865-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Bingyi Yang ◽

Angkana T. Huang ◽

Bernardo Garcia-Carreras ◽

William E. Hart ◽

Andrea Staid ◽

...

Keyword(s):

United States ◽

Home Visiting ◽

Leisure Activities ◽

The United States ◽

Causal Effects ◽

Basic Reproductive Number ◽

Reproductive Number ◽

County Level ◽

Metapopulation Model ◽

Pharmaceutical Interventions

AbstractNon-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (Reff) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median Reff below 1 when combined with either stay at home orders (median Reff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median Reff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

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The Role of Population Mobility and Non-Pharmaceutical Interventions on COVID-19 Infection: A Canadian Case Study of Granger-Causal Relationships

SSRN Electronic Journal ◽

10.2139/ssrn.3805847 ◽

2021 ◽

Author(s):

Myrtha E. Reyna ◽

Boxi Lin ◽

Lehang Zhong ◽

Michael Jongho Moon ◽

Mohammad Kaviul Anam Khan ◽

...

Keyword(s):

Causal Relationships ◽

Population Mobility ◽

Pharmaceutical Interventions

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A metapopulation model for zika virus disease transmission dynamics between linked communities

Physica Scripta ◽

10.1088/1402-4896/ac2bdb ◽

2021 ◽

Author(s):

P M Tchepmo Djomegni ◽

Gabriel Oluwamuyiwa Olupitan ◽

Emile Franc D. Goufo

Keyword(s):

Zika Virus ◽

Disease Transmission ◽

Virus Disease ◽

Transmission Dynamics ◽

Metapopulation Model

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Hydrology-informed metapopulation modeling of liver fluke transmission in the Lawa Lake complex of northeast Thailand

10.1101/569913 ◽

2019 ◽

Author(s):

Tomás M. León ◽

Vichian Plermkamon ◽

Kittiwet Kuntiyawichai ◽

Banchob Sripa ◽

Robert C. Spear

Keyword(s):

Disease Transmission ◽

Liver Fluke ◽

Pathogen Transmission ◽

Transmission Dynamics ◽

Northeast Thailand ◽

Metapopulation Model ◽

Hydrologic Processes ◽

Lake System ◽

Hydrologic Data ◽

Liver Flukes

AbstractWhile hydrologic processes are intuitively understood to influence transmission dynamics of water-related diseases, limited research exists that explicitly links hydrologic and infectious disease data. In the case of the life cycle of liver flukes, hydrology influences several transmission processes that mediate infection risk for multiple hosts. Northeast Thailand is a hotspot for liver fluke transmission and has strong seasonal flooding patterns. A metapopulation model linking local hydrologic processes with transmission of the liver fluke Opisthorchis viverrini in a lake system in northeast Thailand was developed and parameterized using infection data from 2008-2016. A rainfall-runoff model and other hydrologic data were used to assess level of connectivity between villages and the influence of upstream communities on parasite distribution in the study area. Disease transmission was modeled with metapopulations representing six village clusters around the lake using known prevalence data from humans, cats and dogs, snails, and fish. The metapopulation model improved upon the single-village model in its match to historical data patterns for the six village clusters with the introduction of the new time-variable parameters. Results suggest there are three unique hydrologic-epidemiologic regimes within the Lawa Lake system in response to upstream watersheds and risk of overland flooding that contribute to risk for O. viverrini infection. While available data may be insufficient to specifically characterize exact transmission dynamics, the practical implications of such findings are the importance of addressing connectivity for any intermediate host-based intervention. Similar approaches using hydrologic data to assess the impacts of water on pathogen transmission dynamics and inform mechanistic disease transmission models could be applied across other water-related disease systems.

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Genomic epidemiology reveals how restriction measures shaped the SARS-CoV-2 epidemic in Brazil

10.1101/2021.10.07.21264644 ◽

2021 ◽

Author(s):

Marta Giovanetti ◽

Svetoslav Nanev Slavov ◽

Vagner Fonseca ◽

Eduan Wilkinson ◽

Houriiyah Tegally ◽

...

Keyword(s):

Public Health ◽

Latin America ◽

Early Stage ◽

Virus Transmission ◽

Transmission Dynamics ◽

Genomic Epidemiology ◽

Immunization Strategies ◽

Adjacent Country ◽

Time Spread ◽

Local Transmission

Brazil has experienced some of the highest numbers of COVID-19 infections and deaths globally and made Latin America a pandemic epicenter from May 2021. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of local virus transmission dynamics. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and an adjacent country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed, the absence of effective restriction measures led to the local emergence and international spread of Variants of Concern (VOC) and under monitoring (VUM), including the Gamma (P.1) and Zeta (P.2) variants. In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring and providing a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies.

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Individual social contact data and population mobility data as early markers of SARS-CoV-2 transmission dynamics during the first wave in Germany—an analysis based on the COVIMOD study

BMC Medicine ◽

10.1186/s12916-021-02139-6 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Damilola Victoria Tomori ◽

Nicole Rübsamen ◽

Tom Berger ◽

Stefan Scholz ◽

Jasmin Walde ◽

...

Keyword(s):

Survey Data ◽

Social Contact ◽

Transmission Dynamics ◽

Relative Reduction ◽

Population Mobility ◽

Mobility Data ◽

Infection Dynamics ◽

Contact Data ◽

The One ◽

Contact Survey

Abstract Background The effect of contact reduction measures on infectious disease transmission can only be assessed indirectly and with considerable delay. However, individual social contact data and population mobility data can offer near real-time proxy information. The aim of this study is to compare social contact data and population mobility data with respect to their ability to reflect transmission dynamics during the first wave of the SARS-CoV-2 pandemic in Germany. Methods We quantified the change in social contact patterns derived from self-reported contact survey data collected by the German COVIMOD study from 04/2020 to 06/2020 (compared to the pre-pandemic period from previous studies) and estimated the percentage mean reduction over time. We compared these results as well as the percentage mean reduction in population mobility data (corrected for pre-pandemic mobility) with and without the introduction of scaling factors and specific weights for different types of contacts and mobility to the relative reduction in transmission dynamics measured by changes in R values provided by the German Public Health Institute. Results We observed the largest reduction in social contacts (90%, compared to pre-pandemic data) in late April corresponding to the strictest contact reduction measures. Thereafter, the reduction in contacts dropped continuously to a minimum of 73% in late June. Relative reduction of infection dynamics derived from contact survey data underestimated the one based on reported R values in the time of strictest contact reduction measures but reflected it well thereafter. Relative reduction of infection dynamics derived from mobility data overestimated the one based on reported R values considerably throughout the study. After the introduction of a scaling factor, specific weights for different types of contacts and mobility reduced the mean absolute percentage error considerably; in all analyses, estimates based on contact data reflected measured R values better than those based on mobility. Conclusions Contact survey data reflected infection dynamics better than population mobility data, indicating that both data sources cover different dimensions of infection dynamics. The use of contact type-specific weights reduced the mean absolute percentage errors to less than 1%. Measuring the changes in mobility alone is not sufficient for understanding the changes in transmission dynamics triggered by public health measures.

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Modeling the Impact of Unreported Cases of the COVID-19 in the North African Countries

Biology ◽

10.3390/biology9110373 ◽

2020 ◽

Vol 9 (11) ◽

pp. 373

Author(s):

Salih Djilali ◽

Lahbib Benahmadi ◽

Abdessamad Tridane ◽

Khadija Niri

Keyword(s):

Population Movement ◽

Population Mobility ◽

North African ◽

Active Infection ◽

African Countries ◽

The North ◽

North African Countries ◽

The Impact ◽

Second Wave ◽

Epidemic Wave

In this paper, we study a mathematical model investigating the impact of unreported cases of the COVID-19 in three North African countries: Algeria, Egypt, and Morocco. To understand how the population respects the restriction of population mobility implemented in each country, we use Google and Apple’s mobility reports. These mobility reports help to quantify the effect of the population movement restrictions on the evolution of the active infection cases. We also approximate the number of the population infected unreported, the proportion of those that need hospitalization, and estimate the end of the epidemic wave. Moreover, we use our model to estimate the second wave of the COVID-19 Algeria and Morocco and to project the end of the second wave. Finally, we suggest some additional measures that can be considered to reduce the burden of the COVID-19 and would lead to a second wave of the spread of the virus in these countries.

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Migrant Death and Identification

Massacres ◽

10.5744/florida/9781683400691.003.0011 ◽

2018 ◽

pp. 167-183

Author(s):

Krista E. Latham ◽

Alyson O’Daniel ◽

Justin Maiers

Keyword(s):

Economic Theory ◽

Latin America ◽

Social Inequality ◽

Undocumented Migrant ◽

Humanitarian Crisis ◽

Mexico Border ◽

Political Economic ◽

The U.S ◽

Structural Inequalities

Chapter 11 explores undocumented migrant deaths on the U.S.-Mexico border. Recent changes to border policies have led to an increase in migrant deaths. In order to make sense of this humanitarian crisis, political economic theory that considers power and structural inequalities is applied. A careful review demonstrates how, coupled with historical trajectories in Latin America, the rise of neoliberalism has led to increases in social inequality and violence, resulting in increased migration as the oppressed flee in the hopes of finding a different life. Due to the dangerous conditions encountered along the journey, many migrants die every year attempting to find this new life.

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