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In recent years, COVID-19 has evolved into many variants, posing new challenges for disease control and prevention. The Omicron variant, in particular, has been found to be highly contagious. In this study, we constructed and analyzed a mathematical model of COVID-19 transmission that incorporates vaccination and three different compartments of the infected population: asymptomatic (I a) , symptomatic (I s) , and Omicron (I m) . The model is formulated in the Caputo sense, which allows for fractional derivatives that capture the memory effects of the disease dynamics. We proved the existence and uniqueness of the solution of the model, obtained the effective reproduction number, showed that the model exhibits both endemic and disease-free equilibrium points, and showed that backward bifurcation can occur. Furthermore, we documented the effects of asymptomatic infected individuals on the disease transmission. We validated the model using real data from Thailand and found that vaccination alone is insufficient to completely eradicate the disease. We also found that Thailand must monitor asymptomatic individuals through stringent testing to halt and subsequently eradicate the disease. Our study provides novel insights into the behavior and impact of the Omicron variant and suggests possible strategies to mitigate its spread. [ABSTRACT FROM AUTHOR]

The spread of COVID-19 started in late December 2019 and is still ongoing. Many countries around the world have faced an outbreak of COVID-19, including Thailand, which must keep an eye on the spread and find a way to deal with this extreme outbreak. Of course, we are unable to determine the number of people who will contract this disease in the future. Therefore, if there is a tool that helps to predict the outbreak and the number of people infected, it will be able to find preventive measures in time. This paper aims to develop a mathematical model suitable for the lifestyle of the Thai population facing the COVID-19 situation. It has been established that after close contact with an infected person, a group of individuals will be quarantined and non-quarantined. If they contract COVID-19, they will enter the incubation period of the infection. The incubation period is divided into the quarantine class and the exposed class. Afterwards, both classes will move to the hospitalized infected class and the infected class, wherein the infected class is able to spread the disease to the surrounding environment. This study describes both classes in the SQEIRP model based on the population segmentation that was previously discussed. After that, the positive and bounded solutions of the model are examined, and we consider the equilibrium point, as well as the global stability of the disease-free point according to the Castillo-Chavez method. The SQEIRP model is then numerically analyzed using MATLAB software version R2022a. The cumulative percentage of hospitalized and non-hospitalized infections after 7 days after the commencement of the infection was determined to be 11 and 34 percent of the entire population, respectively. The Next-Generation Matrix approach was used to calculate the Basic Reproduction Numbers ( R 0 ). The SQEIRP model's R 0 was 3.78, indicating that one infected individual can result in approximately three additional infections. The results of this SQEIRP model provide a preliminary guide to identifying trends in population dynamics in each class. [ABSTRACT FROM AUTHOR]

Rice blast disease, caused by the fungus Pyricularia oryzae, is one of the diseases that reduce rice yields in Thailand. The fungus's dispersal influences this disease outbreak. This study aims to develop a mathematical model for spore dispersion, namely a non-local diffusion equation in terms of the dispersal kernel, by adding a factor that causes spore dispersion due to rain splash and adjusting the infection term based on weather conditions such as air temperature and relative humidity. The model assessed the existence and uniqueness of solutions by Banach's fixed point theorem and used a finite difference method to solve them. The numerical simulation confirmed the existence and uniqueness part of the analysis. Because the climate data was used effectively for developing the disease, the rice blast disease pandemic was widespread in the study areas. [ABSTRACT FROM AUTHOR]

The conservation strategies of two national parks i.e., Chiltan Hazarganji of Pakistan and Kaeng Krachan of Thailand were compared in this study. It was found that that Kaeng Krachan national park has much better "Zoning schemes" conservation strategies than Chiltan Hazarganji national park. However, the "trophy hunting" and community involvement of Chiltan Hazarganji were also important for conservation of Chiltan Markhor. The best conservation strategies of Kaeng Krachan national park may be attributed not only to awareness of the Thai people about biodiversity conservation but also the strong political will of Thailand's government to promote tourism industry of the country. The study therefore recommends the exchange of information on natural resources conservation between the two countries. [ABSTRACT FROM AUTHOR]