Influencing factors of COVID-19 spreading: a case study of Thailand

Abstract

Aim A novel corona virus disease 2019 was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient. Results The number of infected cases was significant associated (correlation coefficient > 0.7) with economic factor, namely; number of visitors, generated income from both Thai and foreigner tourist (p value <0.01). The influencing factors of slow increased rate were the enforcement and implementation of both central and local government regulation, the strength of the Thai health care system, the culture and social relation, the partnership among various governmental and private sectors. Conclusion We found that the number of tourist and their activities were significant associated with number of infected, confirmed COVID-19 cases. The public education and social supporting were the key roles for regulation enforcement and implementation.

Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi

“…The study finds significant effect of poverty incidence and proportion of elderly (65+ years) people on COVID-19 risk. The results on effect of poverty on COVID-19 risk are consistent with the literature ( Tantrakarnapa, Bhopdhornangkul & Nakhaapakorn, 2020 ; Sarmadi et al, 2020 ), where it was found that high income compared to low income was positively associated with COVID-19 cases. Low risk of COVID-19 among poor people than rich people may be due to the fact that such people are less likely to travel to cities and abroad where they can be exposed to the disease.…”

“…The spread of COVID-19 is driven by environmental factors like temperature and humidity, where cases spike with low temperature and humidity ( Mecenas et al, 2020 ; Eslami & Jalili, 2020 ; Bherwani et al, 2020 ). Demographic and socioeconomic factors like population density, age distribution, income, number of tourists, also play a role in the spread of COVID-19 cases, where high cases are observed with high density, age, income and large number of tourists ( Tantrakarnapa, Bhopdhornangkul & Nakhaapakorn, 2020 ). Density has also been found not to be correlated with COVID-19 cases ( Hamidi, Sabouri & Ewing, 2020 ), contrary to the belief of many that it is positively correlated with COVID-19 cases.…”

Evaluating the Impact of Intervention Strategies on the First Wave and Predicting the Second Wave of COVID-19 in Thailand: A Mathematical Modeling Study

“…Additionally, the number of imported cases can affect the magnitude of an outbreak [ 39 ]. In Thailand, the number of confirmed cases was strongly associated with the number of tourists and their activities [ 40 ]. Therefore, interventions such as travel bans, closing the border, and the 14-day state or alternative quarantine for international travellers should be considered.…”

Factors Affecting the Cases and Deaths of COVID-19 Victims

“…Rate of infection and the fast transmission of the disease is one of the alarming issues of the pandemic. In Thailand, the number of tourists and their activities were found to be significant factors on the number of infected patients from COVID-19 [ 31 ]. In Italy, a tighter lockdown, mobility decreased enough to bring down transmission promptly below the level needed to sustain the epidemic [ 32 ].…”