Background: When a new pathogen emerges, consistent case reporting is critical for public health surveillance. Tracking cases geographically and over time is key for understanding the spread of an infectious disease and effectively designing interventions to contain and mitigate an epidemic. In this paper we describe the reporting systems on COVID-19 in Southeast Asia during the first wave in 2020, and highlight the impact of specific reporting methods.Methods: We reviewed key epidemiological variables from various sources including a regionally comprehensive dataset, national trackers, dashboards, and case bulletins for 11 countries during the first wave of the epidemic in Southeast Asia. We recorded timelines of shifts in epidemiological reporting systems and described the differences in how epidemiological data are reported across countries and timepoints.Results: Our findings suggest that countries in Southeast Asia generally reported precise and detailed epidemiological data during the first wave of the pandemic. Changes in reporting rarely occurred for demographic data, while reporting shifts for geographic and temporal data were frequent. Most countries provided COVID-19 individual-level data daily using HTML and PDF, necessitating scraping and extraction before data could be used in analyses.Conclusion: Our study highlights the importance of more nuanced analyses of COVID-19 epidemiological data within and across countries because of the frequent shifts in reporting. As governments continue to respond to impacts on health and the economy, data sharing also needs to be prioritised given its foundational role in policymaking, and in the implementation and evaluation of interventions.

About the Data:

A year ago, when WHO declared COVID-19 outbreak a pandemic, countries in WHO South-East Asia Region were either responding to their first cases of importation or cluster of cases or keeping a strict vigil against importation of the new coronavirus.

The following months were unprecedented, and for many reasons. Scientists, experts, governments, societies, communities and even individuals responded to the new virus with urgency and measures never witnessed before.

Metadata:

ID: Unique Identifier Country: Name of Country TotalCases: Total Number of cases recorded so far TotalDeaths: Total Deaths recorded so far TotalRecovered: How many people survived ActiveCases: Number of people who currently has the virus TotalCasesPerMillion: How many cases are recorded per million individual TotalDeathsPerMillion: How many deaths recorded per million individual TotalTests: Total number of COVID19 tests conducted RTPCR + RAT + any other tests TotalTestsPerMillion: How many tests were conducted per million individual TotalPopulation: Population of the country

Acknowledgements:

This dataset was collected from: https://www.worldometers.info/coronavirus/#countries

Call For Code:

Fellow Data Scientist and ML engineers, can you identify which countries are doing relatively well and which ones need immediate attention? Your insights can save millions of lives in Asia!

Distribution of predictors according to COVID-19 death status in the southeast region of Brazil, 2020–2023.

IntroductionIn March 2020, the National Center for Advancing Translational Sciences—Clinical and Translational Science Awards (CTSA) Program issued an urgent “Call to Action,” requesting CTSA hubs to accelerate clinical and translational research (C&TR) in response to the COVID-19 public health emergency. The Clinical and Translational Science Institute of Southeast Wisconsin (CTSI) quickly responded by launching a regional research initiative among its eight academic and healthcare partner institutions to nucleate teams around COVID-19 C&TR.MethodsA comprehensive search of COVID-19 funding opportunities, combined with suggestions from CTSI leadership and C&TR investigators, produced a list of 31 distinct C&TR questions that were used to nucleate investigators into teams. A survey was shared with the faculty of all eight partner institutions to solicit interest in joining the teams. Multidisciplinary team formation was based on a novel CTSI model, called the “Team Science-Guided Integrated Clinical and Research Ensemble (Ensemble).” In this model, teams are formed around an unmet patient medical need, based on the intentional recruitment of members from three domains: (1) the clinical and translational research enterprise, (2) the health care systems, and (3) the community of stakeholders. The teams were provided no funding, but received substantial CTSI research and administrative support.ResultsForty-one teams were formed, and 243 investigators participated during the first year of the initiative. Team efforts resulted in the submission of 21 grant proposals, totaling $32,528,297. Three grant proposals were funded, totaling $609,888. The research initiative generated eight publications and had a significant impact on patient health, involving a combined total of 456 research participants. The initiative led to several systemic improvements, by (1) exposing investigators to team science-guided C&TR (Ensembles), (2) increasing inter-institutional and inter-departmental collaborations, (3) creating new partnerships with community organizations, and (4) providing qualitative data on lessons learned.ConclusionThe COVID-19 regional research initiative provided a compelling model of how basic science, clinical/translational, and community researchers can be mobilized for accelerated C&TR to address a public health threat. The initiative demonstrated that the fundamentals of the novel CTSI Ensemble team concept can be leveraged to expedite the formation of highly efficient teams.

Dataset

This dataset was created by Hans Darmawan

Contents

COVID-19 Vaccination: by State: Southeast data was reported at 2.000 Dose in 08 Dec 2024. This records a decrease from the previous number of 682.000 Dose for 07 Dec 2024. COVID-19 Vaccination: by State: Southeast data is updated daily, averaging 24,950.000 Dose from Mar 2020 (Median) to 08 Dec 2024, with 1722 observations. The data reached an all-time high of 2,004,424.000 Dose in 09 Sep 2021 and a record low of 0.000 Dose in 31 Dec 2020. COVID-19 Vaccination: by State: Southeast data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Brazil Premium Database’s Health Sector – Table BR.HLA007: Disease Outbreaks: COVID-19: Vaccination: by Region.

Dataset

This dataset was created by Bob Ivan Leyga

Contents

It is estimated that by the end of 2021 the COVID-19 pandemic had caused around 14.9 million excess deaths worldwide. South-East Asia accounted for the highest number of these deaths with about 5.99 million excess deaths due to the pandemic. This statistic shows the cumulative mean number of excess deaths associated with the COVID-19 pandemic worldwide as of the end of 2021, by region.

Crude and adjusted hazard ratio of COVID-19 death according to the predictors (southeast of Brazil).

Yearly citation counts for the publication titled "COVID-19 and Civil Society in Southeast Asia: Beyond Shrinking Civic Space".

HHS-Official/ah-provisional-covid-19-deaths-counts-by-health-se dataset hosted on Hugging Face and contributed by the HF Datasets community

Multilingual (EN, SV, TR) corpus acquired from the website (https://www.krisinformation.se/) of Emergency Information from Swedish Authorities (15th September 2020). It contains 721 TUs in total.

The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

COVID-19 Vaccination: by State: Southeast: Female data was reported at 0.000 Dose in 08 Dec 2024. This records a decrease from the previous number of 408.000 Dose for 07 Dec 2024. COVID-19 Vaccination: by State: Southeast: Female data is updated daily, averaging 14,580.500 Dose from Mar 2020 (Median) to 08 Dec 2024, with 1722 observations. The data reached an all-time high of 1,022,708.000 Dose in 09 Sep 2021 and a record low of 0.000 Dose in 08 Dec 2024. COVID-19 Vaccination: by State: Southeast: Female data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under Brazil Premium Database’s Health Sector – Table BR.HLA007: Disease Outbreaks: COVID-19: Vaccination: by Region.

Background: By February 2021, the overall impact of coronavirus disease 2019 (COVID-19) in South and Southeast Asia was relatively mild. Surprisingly, in early April 2021, the second wave significantly impacted the population and garnered widespread international attention.Methods: This study focused on the nine countries with the highest cumulative deaths from the disease as of August 17, 2021. We look at COVID-19 transmission dynamics in South and Southeast Asia using the reported death data, which fits a mathematical model with a time-varying transmission rate.Results: We estimated the transmission rate, infection fatality rate (IFR), infection attack rate (IAR), and the effects of vaccination in the nine countries in South and Southeast Asia. Our study suggested that the IAR is still low in most countries, and increased vaccination is required to prevent future waves.Conclusion: Implementing non-pharmacological interventions (NPIs) could have helped South and Southeast Asia keep COVID-19 under control in 2020, as demonstrated in our estimated low-transmission rate. We believe that the emergence of the new Delta variant, social unrest, and migrant workers could have triggered the second wave of COVID-19.

From January to April 2020, the weekly viewing durations of content on WeTV in Southeast Asia increased by *** percent. In comparison, the weekly viewing durations of Vidio increased by ** percent in Southeast Asia from January to April 2020. The dramatic increases in viewing durations were caused by the outbreak of the coronavirus, in which there were periods of total or partial lockdown.

The first round of the Myanmar Household Welfare Survey (MHWS)–a nationwide phone panel consisting of 12,100 households–was implemented between December 2021 and February 2022. The objective of the survey was to collect data on a wide range of household and individual welfare indicators–including wealth, livelihoods, unemployment, food insecurity, diet quality, health shocks, and coping strategies–in a country exceptionally hard hit by conflict, severe economic collapse, and several damaging waves of COVID-19. The respondents interviewed in the MHWS were purposely selected from a large phone database aimed at being representative at the region/state level and urban/rural level in Myanmar. A novel sampling strategy in combination with the development of household and population weights allows for estimates that are nationally, regionally, and urban/rural representative.

Social cognitive and behavioral factors related to COVID-19 prevention by rural vs. urban status in southeastern, Minnesota, N (%).

IntroductionSince February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States.MethodsA retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022.Results and discussionIn this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90 days (n = 19,679), and 13% were readmitted within 30 days (n = 11,912). In logistic regression analyses, Hispanic and non-Hispanic Asian patients were less likely to be readmitted within 90 days (adjusted odds ratio [aOR]: 0.8, 95% confidence interval [CI]: 0.7–0.9, and aOR: 0.8, 95% CI: 0.8–0.8), while non-Hispanic Black patients were more likely to be readmitted (aOR: 1.1, 95% CI: 1.0–1.1, p = 0.002), compared to non-Hispanic White patients. Area deprivation index displayed a clear dose–response relationship to readmission: patients living in the most disadvantaged neighborhoods were more likely to be readmitted within 30 (aOR: 1.1, 95% CI: 1.0–1.2), 60 (aOR: 1.1, 95% CI: 1.2–1.2), and 90 days (aOR: 1.2, 95% CI: 1.1–1.2), compared to patients from the least disadvantaged neighborhoods. Our findings demonstrate the lasting impact of COVID-19, especially among members of marginalized communities, and the increasing burden of COVID-19 morbidity on the healthcare system.