Abstract The global but uneven course of the Covid-19 pandemic highlights the importance of international cooperation and negotiation on such matters as financial assistance, medical equipment provision, vaccine development and distribution, and other pandemic response measures. This article will present a theoretical overview of “health diplomacy” and analyze the case of Vietnam within this framework, showing how the country’s political response to the pandemic demonstrates an increasingly proactive engagement in health diplomacy. The article argues that health diplomacy will become more relevant for international relations in the time to come and that the case of Vietnam might yield valuable lessons.

Context

On December 31, 2019, Chinese officials informed the first case of COVID-19 in Wuhan (China). Around the end of January, 2020, many countries (the U.S., the UK, South Korea, etc.), including Vietnam reported their first COVID-19 cases.

Since then, each country has their own specific strategy to contain the outbreak. Most of the countries have now shifted from the containment (early tracking, isolating the infection sources) to serious mitigation (tactics to reduce transmission) paradigms. Although loosing some F0 cases, Vietnam still has remained safely in the containment stage.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3439828%2Fbe8a17529fc1b48e3c44be94afe75529%2FVietnam_trend.png?generation=1588195825303050&alt=media" alt="">

Vietnam currently has only 270 COVID-19 confirmed cases in total with NO FATALITIES. And now, Vietnam is on its 13 straight days with no new local transmitted cases and 5 straight days without any imported cases (Updated on April 29, 2020). This leave us so many question to ask.

1. What has happened in Vietnam? Was the number of COVID-19 cases reported by Vietnamese officials undercounted? Did testing work well in Vietnam?

2. Did the Vietnam government suppressed information about their local COVID-19 pandemic? And if not, with such the 'real' low number of cases and no death, how did Vietnam contain the virus?

3. What did we know about the Vietnam COVID-19 patients? Is there characteristics of the patients that helps slow down the infection rate in Vietnam?

One remarkable thing about Vietnam health care system is the fact that privacy laws are not as stringent as in the US, Canada or the EU. Therefore, COVID-19 patient data in Vietnam is publicly available. For some cases, detail gets seriously down to their names, their personal contacts, daily activities and even their habits.

To help answer some of the above questions, I decided to collect the Vietnam data and study it independently using all the information available on the internet. I hope this dataset will provide some insights into the COVID-19 pandemic at the specific country level.

Collection methodology

• Data was acquired by web scrapping with manually curated from the Vietnam Ministry of Health's website (https://ncov.moh.gov.vn/) and other mainstream media in Vietnam (which were cited specifically in each data row).
• The world data was obtained from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). https://github.com/CSSEGISandData/COVID-19

Disclaimer:

• This is my personal work with no link to any organization. Although this analysis is data-driven, my comments reflect my personal perspectives.
• My results are based on the data collected from the Vietnam Health Ministry website and the mainstream media in Vietnam. The data might be biased and reflects what is publicly available on the internet. However, it can served as a good reference for someone who are curious about the COVID-19 pandemic in Vietnam. Some information conflicts (about the data) would be explained in detail in the exploration notebook that goes together with this dataset.

A full report and visualization for this dataset can be found in my Medium site.

Dataset was updated until May 10, 2020.

The data set provides numbers of COVID-19 infections in Vietnam and some neighboring countries in Asia. In the data set in Vietnam, there is a classification of the total number of new cases, new cases and new infections in the community. The number of infections in the community is the number of unknown infections. The case data is published on a daily basis and is aggregated to the time of current statistics.

As of November 15, 2023, Ha Noi had 1,646,923 confirmed cases of COVID-19, followed by 629,018 cases in Ho Chi Minh City. There were 11,619,990 cumulative confirmed cases of coronavirus in Vietnam. The country is currently responding to a new COVID-19 variant with aggressive contact tracing and mass testing.

COVID-19 development in Ha Noi The first four infections in the country’s capital were one 26-year-old female, one 27-year-old male, one 64-year-old female and one 61-year-old male. The 26-year-old female was patient 17, who returned from Europe on flight VN0054 from Vietnam Airlines. There were 130 people in close contact with patient 17 and another 226 people identified as having been in close contact with the aforementioned 130 people. Those who were in close contact to patient 17 were brought into quarantine, and the residential area was put under lockdown.

Measures during COVID-19 in Ho Chi Minh City

The People’s Council of Ho Chi Minh City has approved a financial package of 2.75 trillion Vietnamese dong to fight the COVID-19 epidemic. The financial package will be used to provide meal subsidies to people under quarantine, as well as daily allowances for medical workers, military staff and other forces that are engaged in the work of epidemic control. Part of the financial package will be reserved for a possible increase in patients and people that would need to be quarantined. Furthermore, teachers and staff members who would lose income during this time but are not entitled to unemployment benefits will receive one million Vietnamese dong in support each month.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3553471%2F3e65ec900106b13b3042fc7d424bd569%2FVn%20Map.png?generation=1584296146474224&alt=media" alt="">

Context

Vietnam SARS-CoV-2 | COVID-19 Compiled Data from Several Reliable Sources such as VnExpress.net, Ministry of Health.

Content

Brief summary of cases 17 - 53. 14/3/2020: Confirmed: 53, Recovered: 16, Death: 0

Column Headers: - Date: Date of reporting case - Case: Case ID - Gender - Age - Origin: Last known location before reported - (Potential) Infection Source: Additional travel information - Current Location: Last known treatment location - Confirmed: Tested Positive - Recovered: Recovered | Tested Negative | No Longer Quarantined - Death - Source Information: References

Acknowledgements

NA

Inspiration

I'm interested in SARS-CoV-2 | COVID-19 spread.

After the COVID-19 outbreak, the Ministry of Planning and Investment discussed two possible scenarios and its impact on the country's services sector. In the case that the coronavirus can be contained in the second quarter of 2020, the services sector was projected to increase by 6.47 percent. In the same scenario, the agriculture sector will grow at a rate of 2.35 percent and the industry sector will grow at a rate of 7.1 percent.

After the COVID-19 outbreak, the Ministry of Planning and Investment discussed two possible scenarios and its impact on the country's GDP. The initial GDP growth projection before the virus outbreak was at 6.8 percent. In the case that the coronavirus can be contained in the second quarter of 2020, the GDP was projected to increase by only 6.09 percent. In the same scenario, the agriculture will grow at a rate of 2.35 percent, the industry sector will grow at a rate of 7.1 percent and the services sector will grow at a rate of 6.47 percent.

Disease Severity and Vaccination Propensity: A COVID-19 Case Study From Vietnam

After the COVID-19 outbreak, the Ministry of Planning and Investment discussed two possible scenarios and its impact on the country's agriculture sector. In the case that the coronavirus can be contained in the second quarter of 2020, the agriculture sector was projected to increase by 2.35 percent. In the same scenario, the industry sector will grow at a rate of 7.1 percent and the services sector will grow at a rate of 6.47 percent. According to the ministry, the agriculture sector will be hit hardest by the virus outbreak.

After the COVID-19 outbreak, the Ministry of Planning and Investment discussed two possible scenarios and its impact on the country's industry sector. In the case that the coronavirus can be contained in the second quarter of 2020, the industry sector was projected to increase by 7.1 percent. In the same scenario, the agriculture sector will grow at a rate of 2.35 percent and the services sector will grow at a rate of 6.47 percent.

Government intervention selection during the COVID-19 outbreak is viewed as a Multi-Criteria Decision Making (MCDM) problem in a hazy and uncertain environment in which governments and medical communities adjust their priorities in response to emerging issues and the efficacy of interventions implemented in various countries. The purpose of this study is to propose a novel hybrid Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS-F) model to assist stakeholders such as governors and policymakers in prioritizing government interventions to address the COVID-19 outbreak. The SF-AHP is used to compare criteria pairwise and calculate the relative weight of each criterion. The WASPAS-F technique is then used to rank 15 possible intervention strategies. In Vietnam, an empirical case study was done. Additionally, the weights of strategies at the local and global levels, as well as their ranking order, are computed. The supplementary data concludes 3 files: 1. SF-AHP to determine the relative weights of 5 criteria 2. SF- AHP in complete and partial approaches 3.WASPAS-F Results

Prepared by Lan Thuong Nguyen, a PhD. Candidate from the International Doctoral Program in Asia-Pacific Studies (IDAS) at National Chengchi University (NCCU), at the Center for Asia-Pacific Resilience and Innovation (CAPRi).

Lan Thuong Nguyen is a co-author of this project alongside an American researcher, Dr. Yen Pottinger, who has clearly defined responsibilities. Her role is sourcing and analyzing documents related to public health policies during the COVID-19 pandemic, vaccination promotion programs, communication strategies against COVID-19, and research articles and reports on vaccine acceptance rates among the Vietnamese population. Additionally, she examines public sentiment regarding the government's COVID-19 strategies and other relevant information. As a result, she searched, curated, and compiled the datasets and stored them in the depositar. She is also responsible for overseeing the storage, management, and, if necessary, customization of these data. The management process does not require additional resources or incur storage or data preparation costs. The datasets will be shared via the repository, with access requests managed by Lan Thuong Nguyen. No personal data is included in the datasets.

The project titled "Misinformation, Disinformation, and Vaccine Hesitancy in Vietnam" forms part of a broader series of studies analyzing vaccine hesitancy across various countries in the Asia-Pacific region. This research examines both the historical context and the impact of the COVID-19 pandemic, with a particular focus on the influence of misinformation and disinformation on governmental and civil society efforts to promote vaccination. It belongs to the Center for Asia-Pacific Resilience and Innovation (CAPRi). The project has been completed and posted on the Center for Asia-Pacific Resilience and Innovation (CAPRi) website.

In this case, the project aims to analyze the factors contributing to vaccine hesitancy in Vietnam, with a particular focus on the influence of misinformation and disinformation. It will examine the historical context, the role of digital and social media, and the effectiveness of governmental and public health responses in addressing these challenges during the COVID-19 pandemic. The project contains metadata on the Vietnamese vaccination program and focuses on the country's public health policy, communication strategies, and vaccination experiences.

The dataset below is part of this project. It introduces the COVID-19 prevention policies, provides an overview of the current status, and compiles academic research on vaccine acceptance, the prevalence of misinformation, and how governments are addressing these issues.

Files must be downloaded to use the entire dataset (depositar only provides limited data previews). This dataset comprises one ZIP file, one XLSX spreadsheet, and one PDF file. The ZIP files contain academic research and documents on experiences propagating COVID-19 vaccination in Vietnamese and English. They are collected for reference in this project, and each article/ research paper/ report is attached with links in this ZIP file. The XLSX spreadsheet is a collection of public health policies applicable to the country made by the author to understand how the Vietnamese government prevented, combated, and governed the anti-COVID-19 campaign. It is used for reference purposes. The PDF file is a literature review written by the author with detailed citations and references. It is conducted based on the requirements of the project manager to have an overview of Vietnam's public health policy.

In its present state, the dataset is presented primarily in Vietnamese and English.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.-- Esri COVID-19 Trend Report for 3-9-2023 --0 Countries have Emergent trend with more than 10 days of cases: (name : # of active cases) 41 Countries have Spreading trend with over 21 days in new cases curve tail: (name : # of active cases)Monaco : 13, Andorra : 25, Marshall Islands : 52, Kyrgyzstan : 79, Cuba : 82, Saint Lucia : 127, Cote d'Ivoire : 148, Albania : 155, Bosnia and Herzegovina : 172, Iceland : 196, Mali : 198, Suriname : 246, Botswana : 247, Barbados : 274, Dominican Republic : 304, Malta : 306, Venezuela : 334, Micronesia : 346, Uzbekistan : 356, Afghanistan : 371, Jamaica : 390, Latvia : 402, Mozambique : 406, Kosovo : 412, Azerbaijan : 427, Tunisia : 528, Armenia : 594, Kuwait : 716, Thailand : 746, Norway : 768, Croatia : 847, Honduras : 1002, Zimbabwe : 1067, Saudi Arabia : 1098, Bulgaria : 1148, Zambia : 1166, Panama : 1300, Uruguay : 1483, Kazakhstan : 1671, Paraguay : 2080, Ecuador : 53320 Countries may have Spreading trend with under 21 days in new cases curve tail: (name : # of active cases)61 Countries have Epidemic trend with over 21 days in new cases curve tail: (name : # of active cases)Liechtenstein : 48, San Marino : 111, Mauritius : 742, Estonia : 761, Trinidad and Tobago : 1296, Montenegro : 1486, Luxembourg : 1540, Qatar : 1541, Philippines : 1915, Ireland : 1946, Brunei : 2010, United Arab Emirates : 2013, Denmark : 2111, Sweden : 2149, Finland : 2154, Hungary : 2169, Lebanon : 2208, Bolivia : 2838, Colombia : 3250, Switzerland : 3321, Peru : 3328, Slovakia : 3556, Malaysia : 3608, Indonesia : 3793, Portugal : 4049, Cyprus : 4279, Argentina : 5050, Iran : 5135, Lithuania : 5323, Guatemala : 5516, Slovenia : 5689, South Africa : 6604, Georgia : 7938, Moldova : 8082, Israel : 8746, Bahrain : 8932, Netherlands : 9710, Romania : 12375, Costa Rica : 12625, Singapore : 13816, Serbia : 14093, Czechia : 14897, Spain : 17399, Ukraine : 19568, Canada : 24913, New Zealand : 25136, Belgium : 30599, Poland : 38894, Chile : 41055, Australia : 50192, Mexico : 65453, United Kingdom : 65697, France : 68318, Italy : 70391, Austria : 90483, Brazil : 134279, Korea - South : 209145, Russia : 214935, Germany : 257248, Japan : 361884, US : 6440500 Countries may have Epidemic trend with under 21 days in new cases curve tail: (name : # of active cases) 54 Countries have Controlled trend: (name : # of active cases)Palau : 3, Saint Kitts and Nevis : 4, Guinea-Bissau : 7, Cabo Verde : 8, Mongolia : 8, Benin : 9, Maldives : 10, Comoros : 10, Gambia : 12, Bhutan : 14, Cambodia : 14, Syria : 14, Seychelles : 15, Senegal : 16, Libya : 16, Laos : 17, Sri Lanka : 19, Congo (Brazzaville) : 19, Tonga : 21, Liberia : 24, Chad : 25, Fiji : 26, Nepal : 27, Togo : 30, Nicaragua : 32, Madagascar : 37, Sudan : 38, Papua New Guinea : 38, Belize : 59, Egypt : 60, Algeria : 64, Burma : 65, Ghana : 72, Haiti : 74, Eswatini : 75, Guyana : 79, Rwanda : 83, Uganda : 88, Kenya : 92, Burundi : 94, Angola : 98, Congo (Kinshasa) : 125, Morocco : 125, Bangladesh : 127, Tanzania : 128, Nigeria : 135, Malawi : 148, Ethiopia : 248, Vietnam : 269, Namibia : 422, Cameroon : 462, Pakistan : 660, India : 4290 41 Countries have End Stage trend: (name : # of active cases)Sao Tome and Principe : 1, Saint Vincent and the Grenadines : 2, Somalia : 2, Timor-Leste : 2, Kiribati : 8, Mauritania : 12, Oman : 14, Equatorial Guinea : 20, Guinea : 28, Burkina Faso : 32, North Macedonia : 351, Nauru : 479, Samoa : 554, China : 2897, Taiwan* : 249634 -- SPIKING OF NEW CASE COUNTS --20 countries are currently experiencing spikes in new confirmed cases:Armenia, Barbados, Belgium, Brunei, Chile, Costa Rica, Georgia, India, Indonesia, Ireland, Israel, Kuwait, Luxembourg, Malaysia, Mauritius, Portugal, Sweden, Ukraine, United Kingdom, Uzbekistan 20 countries experienced a spike in new confirmed cases 3 to 5 days ago: Argentina, Bulgaria, Croatia, Czechia, Denmark, Estonia, France, Korea - South, Lithuania, Mozambique, New Zealand, Panama, Poland, Qatar, Romania, Slovakia, Slovenia, Switzerland, Trinidad and Tobago, United Arab Emirates 47 countries experienced a spike in new confirmed cases 5 to 14 days ago: Australia, Austria, Bahrain, Bolivia, Brazil, Canada, Colombia, Congo (Kinshasa), Cyprus, Dominican Republic, Ecuador, Finland, Germany, Guatemala, Honduras, Hungary, Iran, Italy, Jamaica, Japan, Kazakhstan, Lebanon, Malta, Mexico, Micronesia, Moldova, Montenegro, Netherlands, Nigeria, Pakistan, Paraguay, Peru, Philippines, Russia, Saint Lucia, Saudi Arabia, Serbia, Singapore, South Africa, Spain, Suriname, Thailand, Tunisia, US, Uruguay, Zambia, Zimbabwe 194 countries experienced a spike in new confirmed cases over 14 days ago: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea - South, Kosovo, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Taiwan*, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, US, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza, Yemen, Zambia, Zimbabwe Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.

After the COVID-19 outbreak, the Ministry of Planning and Investment discussed two possible scenarios and its impact on the country's trade turnover. In the case that the coronavirus can be contained in the second quarter of 2020, the export turnover was projected to decrease by 20 percent while the import turnover will decrease by 16 percent. In the same scenario, the country's GDP will increase by 6.27 percent.