Helena Legido-Quigley and colleagues examine the barriers that migrants face in accessing healthcare and argue they are counterproductive for host countries

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Background. Effectiveness of personal protective measure against COVID-19 infection is largely unknown. Methods. We conducted a retrospective case-control study, using a cohort of contact tracing records in Thailand. A total of 1,050 asymptomatic contacts of COVID-19 patients between 1 and 31 March 2020 were retrospectively interviewed by phone about their protective measures against COVID-19 infection. Cases were defined as asymptomatic contacts who were diagnosed with COVID-19 by 21 April 2020. Multilevel mixed-effect logistic regression models were used Findings. Overall, 211 (20%) were diagnosed with COVID-19 by 21 Apr 2020 (case group) while 839 (80%) were not (control group). Fourteen percent of cases (29/210) and 24% of controls (198/823) reported wearing either non-medical or medical masks all the time during the contact period. Wearing masks all the time (adjusted odds ratio [aOR] 0.23; 95%CI 0.09-0.60) was independently associated with lower risk of COVID-19 infection compared to not wearing masks, while wearing masks sometimes (aOR 0.87; 95%CI 0.41-1.84) was not. Shortest distance of contact >1 meter (aOR 0.15; 95%CI 0.04-0.63), duration of close contact ≤15 minutes (aOR 0.24; 95%CI 0.07-0.90) and washing hands often (aOR 0.33; 95%CI 0.13-0.87) were significantly associated with lower risk of infection. Sharing a cigarette (aOR 3.47; 95%CI 1.09-11.02) was associated with higher risk of infection. Those who wore masks all the time were more likely to wash hands and practice social distancing. We estimated that if everyone wore a mask all the time, washed hands often, did not share a dish, cup or cigarette, maintained distances >1 meter and spent ≤15 minutes with close contacts, cases would have been reduced by 84%. Interpretation. Our findings support consistently wearing masks, washing hands, and social distancing in public to protect against COVID-19 infections. Combining measures could substantially reduce infections in Thailand.

The objective of this study is to predict the volume of the elderly in different health status categories in Thailand in the next ten years (2020–2030). Multistate modelling was performed. We defined four states of elderly patients (aged ≥ 60 years) according to four different levels of Activities of Daily Living (ADL): social group; home group; bedridden group; and dead group. The volume of newcomers was projected by trend extrapolation methods with exponential growth. The transition probabilities from one state to another was obtained by literature review and model optimization. The mortality rate was obtained by literature review. Sensitivity analysis was conducted. By 2030, the number of social, home, and bedridden groups was 15,593,054, 321,511, and 152,749, respectively. The model prediction error was 1.75%. Sensitivity analysis with the change of transition probabilities by 20% caused the number of bedridden patients to vary from between 150,249 and 155,596. In conclusion, the number of bedridden elders will reach 153,000 in the next decade (3 times larger than the status quo). Policy makers may consider using this finding as an input for future resource planning and allocation. Further studies should be conducted to identify the parameters that better reflect the transition of people from one health state to another.

Introduction Necrotizing fasciitis (NF) is a rare skin and soft-tissue bacterial infection with high morbidity and mortality. Knowledge about the prevalence and incidence of NF in Thailand is quite sparse. The objective of this study was to determine the prevalence of NF in Thailand and factors that may be potentially associated with NF morbidity and mortality. Methods A cross-sectional study using secondary data from Thailand’s national health databases between 2014 and 2018 was conducted. Descriptive statistics using median and percentage formats were used. This was complemented by multivariable logistic regression to determine the association between various factors (such as age and underlying diseases) with NF morbidity and mortality. Univariate spatial data analysis was exercised to identify the geographical hot spots in which the disease appeared. Results During 2014–2018, we found 90,683 NF cases. About 4.86% of the cases died. The median age for all cases was 59.39 years old. The annual incidence of NF demonstrated an upward trend (from 26.08 per 100,000 population in 2014 to 32.64 per 100,000 population in 2018). The monthly incidence was highest between May and August. A high incidence cluster (as indicated by local Moran’s I) was found in the north-eastern region of Thailand. The most infected sites were on the ankles and feet (43.18%) with an amputation rate of 7.99% in all cases. Multivariable logistic regression indicated that the significant risk factor for amputation was a presence of underlying diseases, namely diabetes (OR 7.94, 95% CI 7.34–8.61). Risk factors for mortality included being elderly (OR 1.82, 95% CI 1.68–1.98) and a presence of underlying hypertension (OR 1.16, 95% CI 1.07–1.27), cirrhosis (OR 4.67, 95% CI 4.17–5.21), and malignancy (OR 1.88, 95% CI 1.55–2.26). Discussion and Conclusion As the elderly and those with chronic underlying diseases are likely to face non-preferable health outcomes from NF, healthcare providers should pay great attention to these groups of patients. Early and intensive treatment might be considered in these groups of patients. Further studies that aim to validate the volume of actual NF cases and reported NF cases are recommended.