As of March 17, 2024, Thailand had approximately 4.76 million confirmed COVID-19 cases. In that same period, there were 34,576 deaths from COVID-19 in the country.

Impact on the economy in Thailand The Thai economy was heavily impacted during the peak of the pandemic. Various restrictions were imposed in the country, resulting in businesses being temporarily interrupted or even permanently shut down. This resulted in a marked decrease in the gross domestic product (GDP) in 2020. One of the most impacted industries in Thailand was tourism. For months, Thailand had exercised regulations for visitors, such as quarantining, causing the tourism contribution to GDP to drop significantly.

Impact on the society in Thailand The COVID-19 pandemic also impacted the ways of life of Thai people. Apart from additional concerns for their health, Thai people had to adapt to changes in their daily lives. Some key changes include the increasing popularity of online shopping, cashless payments, online education, and even working from home. In January 2023, a survey conducted on online shopping behavior in Thailand suggested that the majority of Thais have shopped online more. Working from home also became the norm for many employees during the pandemic. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Thailand recorded 4736356 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Thailand reported 33989 Coronavirus Deaths. This dataset includes a chart with historical data for Thailand Coronavirus Cases.

In past 24 hours, Thailand, Asia had N/A new cases, N/A deaths and N/A recoveries.

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2019 Novel Coronavirus COVID-19 (2019-nCoV) Visual Dashboard and Map:
https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

• Confirmed Cases by Country/Region/Sovereignty
• Confirmed Cases by Province/State/Dependency
• Deaths
• Recovered

Downloadable data:
https://github.com/CSSEGISandData/COVID-19

Additional Information about the Visual Dashboard:
https://systems.jhu.edu/research/public-health/ncov

This Project Tycho dataset includes a CSV file with COVID-19 data reported in THAILAND: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

Characteristics of daily new confirmed COVID-19 cases across the five epidemic stages in Thailand.

According to a survey by Tourism Authority of Thailand about travel behaviors during the coronavirus (COVID-19) pandemic in *********, approximately ** percent of Thai respondents stated that they felt insecured in the domestic tourism because there were a large number of COVID-19 cases and the virus could not be properly controlled in Thailand. Meanwhile, around *** percent of the respondents stated that the COVID-19 measures in the country were not strict enough.

Additional file 1. Table S1: Rapid antigen test in 60 SARS-CoV-2 RT-PCR-positive cases. Characteristics of each COVID-19 Thai case (n=60) including gender, age, initial diagnosis, specimen type, Ct-value of RT-PCR (E, RdRp, N), RT-PCR result, Standard Q COVID-19 Ag test result, and time from symptom onset to laboratory test are demonstrated. Continuous data were presented in mean, standard deviation (SD), median, and range (min, max).

Infected cases and deaths caused by COVID-19 in Sweden, Denmark and Thailand on 31 July 2020.

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Additional file 2. Table S2: Rapid antigen test in 394 SARS-CoV-2 RT-PCR-negative cases. Characteristics of each SARS-CoV-2 RT-PCR-negative case (n=394) including gender, initial diagnosis, specimen type, Ct-value of RT-PCR (E, RdRp, N), RT-PCR result, Standard Q COVID-19 Ag test result, and time from symptom onset to laboratory test are demonstrated. Continuous data were presented in mean, standard deviation (SD), median, and range (min, max).

At the beginning of 2020, the tourism industry across the Asia Pacific region experienced the consequences of the unexpected outbreak of the novel coronavirus (COVID-19). Indonesia displayed a decrease of **** percent in terms of its tourist arrivals. The likes of China, Vietnam, and Thailand all demonstrated dramatic tourist arrival decreases.

Travel cancellations

The outbreak of COVID-19, a respiratory lung infection, originating in Wuhan, China, began to spread just before the Chinese New Year of 2020. Consequently, travel restrictions and increased infection cases hindered plans over the festive period. This in turn resulted in both domestic and international travel cancellations and subsequent losses to the tourism industry. As anxiety over the COVID-19 outbreak grew in 2020, citizens of the Asia Pacific region even stated that flights from China should be banned. Importance of Chinese tourism in Asia Pacific

China is renowned for its economic dominance within the Asia Pacific region. Its thriving economy has allowed for an increased level of affluence among its citizens. Wage increases have allowed Chinese people to travel more frequently, with many opting to travel within the Asia Pacific region. Through increased domestic tourism, many countries across Asia Pacific have come to rely on Chinese tourism to support their respective tourism industries. Interestingly, Chinese tourism alone made great contributions to many of the Asia Pacific GDPs in 2018. As the tourism industry represents a significant part of the GDPs in Hong Kong, Singapore, and Thailand, it is believed that these economies have suffered greatly due to the COVID-19 outbreak. Although there have been outbreaks of infection previously, which have disrupted the tourism industry in Asia Pacific, none have been quite as severe as the COVID-19 outbreak. This is likely due to the fact that previously Asia Pacific tourism industries were not as reliant on Chinese tourism as they have been in recent years.

Long COVID classify by age group after discharge at one-year follow up (n = 331).

Socio-demographic characteristic of COVID-19 patients classifies by status on July 2021 to December 2021(n = 604).

Abstract

The second round in 2020 of the Rapid Needs Assessment (RNA)/Cash-Based Intervention Post-Distribution (CBI PDM) Monitoring Household Survey was conducted in Thailand from October to November 2020. The RNA and PDM were designed as a phone-based survey targeting urban refugees and asylum seekers in Thailand to assess their needs and evaluate the effectiveness of the CBI program in light of COVID-19.

UNHCR Thailand and its partners work to ensure that the protection needs of urban refugees and asylum seekers are met during the COVID-19 pandemic. Having observed increased levels of vulnerability relating to restrictions on movement, loss of livelihood opportunities and access to healthcare, the RNA aims to strengthen the understanding of the situation, need and vulnerabilities of the forced displaced population. This survey focuses on COVID-19 knowledge, experience, behavior and norms, health, education, employment, and access to basic necessities. The findings aim to provide evidence to evaluate and design protection and programme interventions.

Since May 2016, UNHCR Thailand has been using multi-purpose CBI PDM to provide protection, assistance, and services to the most vulnerable refugees in the urban areas. The number of urban refugees approaching UNHCR for financial support has more than doubled since the onset of the COVID-19 pandemic. To ensure that UNHCR's multi-purpose CBI framework for urban refugees in Thailand is effective, the monitoring was conducted simultaneously with the RNA. PDM is a mechanism to collect and understand refugees' feedback on the quality, sufficiency, utilization, and effectiveness of the cash assistance. The findings of the PDM support the assessment of the impact of CBI for urban refugees in Thailand affected by the COVID-19 pandemic and the appropriateness of funding levels, distribution modalities and the use of cash to support refugees.

Geographic coverage

The survey covers all urban refugees and asylum seekers.

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The two parts of the survey were sampled differently as their sampling universe differs. Both samples were drawn from UNHCR's registration database:

1. Post-Distribution Monitoring: The total number of beneficiaries households of Cash-Based Interventions in April 2020 was 5,124. For this part of the survey (CBI PDM), a random sample of 122 refugee households was drawn from all vulnerable urban refugee households registered to receive cash assistance.
2. Rapid Needs Assessment: In addition to the 89 sampled households, who were also answering this part of the survey, a random sample of 91 households, who were not receiving cash assistance, was selected from all urban refugees and asylum seekers registered with UNHCR (5,286).

Sampling deviation

There were some language barriers for some groups that were intended to survey during the RNA/PDM, in particular Vietnamese Montagnard refugees, who could not speak Vietnamese. Also, a Jarai interpreter, who has experience in translating surveys for UNHCR in Thailand was not able to translate the survey. Eventually, these sampled households were dropped and replaced with respondents, who could speak Vietnamese. It is worth noting that there is a large portion of Vietnamese Montagnard, who cannot speak Vietnamese among the urban refugee and asylum seeker population in Thailand (up to 30%). In addition to the described language barriers, few Vietnamese Montagnard refugees also were not able to respond to interview questions due to health issues.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Response rate

The number of cases that could not be reached was slightly higher (18%) in comparison to what was initially planned (10-15%), which was attributed to the COVID-19 situation. Among the cases which refused to be surveyed, half of them cited that they had already been interviewed during the May 2020 RNA-PDM exercise and could not foresee any benefits of participating in a second survey. Others reported that the interview duration was too long and in a few isolated cases, that they could not participate due to work commitments.

Data. Raw dataset (de-identified) used for analysis.

The COVID-19 pandemic has affected millions of individuals worldwide. Pain has emerged as a significant post-COVID-19 symptom. This study investigated the incidence, characteristics, and risk factors of post-COVID chronic pain (PCCP) in Thailand. A cross-sectional study was conducted in participants who had been infected, including those hospitalized and monitored at home by SARS-CoV-2 from August to September 2021. Data were collected for screening from medical records, and phone interviews were done between 3 to 6 months post-infection. Participants were classified into 1) no-pain, 2) PCCP, 3) chronic pain that has been aggravated by COVID-19, or 4) chronic pain that has not been aggravated by COVID-19. Pain interference and quality of life were evaluated with the Brief Pain Inventory and EuroQol Five Dimensions Five Levels Questionnaire. From 1,019 participants, 90% of the participants had mild infection, assessed by WHO progression scale. The overall incidence of PCCP was 3.2% (95% CI 2.3–4.5), with 2.8% (95% CI 2.0–4.1) in mild infection, 5.2% (95% CI 1.2–14.1) in moderate infection and 8.5% (95% CI 3.4–19.9) in severe infection. Most participants (83.3%) reported pain in the back and lower extremities and were classified as musculoskeletal pain and headache (8.3%). Risk factors associated with PCCP, included female sex (relative risk [RR] 2.2, 95% CI 1.0–4.9) and greater COVID-19 severity (RR 3.5, 95% CI 1.1–11.7). Participants with COVID-19-related exacerbated chronic pain displayed higher pain interferences and lower utility scores than other groups. In conclusion, this study highlights the incidence, features, and risk factors of post-COVID chronic pain (PCCP) in Thailand. It emphasizes the need to monitor and address PCCP, especially in severe cases, among females, and individuals with a history of chronic pain to improve their quality of life in the context of the ongoing COVID-19 pandemic.

Comprehensive analysis of physical and mental component summaries (PCS and MCS) across demographic and clinical subgroups of COVID-19 patients.

Factors associated with physical and mental component summary (PCS and MCS) scores in hospitalized COVID-19 patients.