New evidence has emerged regarding when to commence antiretroviral therapy (ART), optimal treatment regimens, management of HIV co-infection with opportunistic infections, and management of ART failure. The 2014 guidelines were developed by the collaborations of the Department of Disease Control, Ministry of Public Health (MOPH) and the Thai AIDS Society (TAS). One of the major changes in the guidelines included recommending to initiating ART irrespective of CD4 cell count. However, it is with an emphasis that commencing HAART at CD4 cell count above 500 cell/mm3 is for public health, in term of preventing HIV transmission and personal benefit. In tuberculosis co-infected patients with CD4 cell counts ≤50 cells/mm3 or with CD4 cell counts >50 cells/mm3 who have severe clinical disease, ART should be initiated within 2 weeks of starting tuberculosis treatment. The preferred initial ART regimen in treatment naïve patients is efavirenz combined with tenofovir and emtricitabine or lamivudine. Plasma HIV viral load assessment should be done twice a year until achieving undetectable results; and will then be monitored once a year. CD4 cell count should be monitored every 6 months until CD4 cell count ≥350 cells/mm3 and with plasma HIV viral load 1,000 copies/mL while on ART. Ritonavir-boosted lopinavir or atazanavir in combination with optimized two nucleoside-analogue reverse transcriptase inhibitors is recommended after initial ART regimen failure. Long-term ART-related safety monitoring has also been included in the guidelines.

It is important to focus on adherence to antiretroviral therapy (ART) and health problems of travellers living with HIV (TLWHIV) during travel. This study was conducted to investigate factors related to adherence and health problems among TLWHIV. This multicentre, cross-sectional observational study was conducted among TLWHIV in university hospitals from August 2019 to July 2020. Factors associated with adherence to ART were evaluated using a logistic regression model. Health problems and risk exposure were also examined among participants during travel. Of 321 TLWHIV, 20 (6.23%) showed moderate-to-poor adherence, among whom 3 (15%) had viral rebound after travelling. Travellers frequently missed ART during the first 3 days of their trip. International destination was associated with moderate-to-poor adherence. In total, 237 (73.8%) travellers reported health problems during travel, among whom 36 required medical attention. Sexual or sharp exposure was found in <5% of travellers during travel. Approximately 95% of Thai TLWHIV had good ART adherence. International destination was the major factor determining adherence. TLWHIV should be encouraged to seek pretravel consultation. Healthcare providers should discuss health risk prevention and teach about ART dosing during travel to enhance adherence and minimise toxicity.

Hospital workers are at high risk of contact with COVID-19 patients. Currently, there is no evidence-based, comprehensive risk assessment tool for healthcare-related exposure; so, we aimed to identify independent factors related to COVID-19 infection in hospital workers following workplace exposure(s) and construct a risk prediction model. We analyzed the COVID-19 contact tracing dataset from 15 July to 31 December 2021 using multiple logistic regression analysis, considering exposure details, demographics, and vaccination history. Of 7146 included exposures to confirmed COVID-19 patients, 229 (4.2%) had subsequently tested positive via RT-PCR. Independent risk factors for a positive test were having symptoms (adjusted odds ratio 4.94, 95%CI 3.83–6.39), participating in an unprotected aerosol-generating procedure (aOR 2.87, 1.66–4.96), duration of exposure >15 min (aOR 2.52, 1.82–3.49), personnel who did not wear a mask (aOR 2.49, 1.75–3.54), exposure to aerodigestive secretion (aOR 1.5, 1.03–2.17), index patient not wearing a mask (aOR 1.44, 1.01–2.07), and exposure distance <1 m without eye protection (aOR 1.39, 1.02–1.89). High-potency vaccines and high levels of education protected against infection. A risk model and scoring system with good discrimination power were built. Having symptoms, unprotected exposure, lower education level, and receiving low potency vaccines increased the risk of laboratory-confirmed COVID-19 following healthcare-related exposure events.

Abacavir and rilpivirine are alternative antiretroviral drugs for treatment-naïve HIV-infected patients. However, both drugs are only recommended for the patients who have pre-treatment HIV RNA <100,000 copies/mL. In resource-limited settings, pre-treatment HIV RNA is not routinely performed and not widely available. The aims of this study are to determine factors associated with pre-treatment HIV RNA <100,000 copies/mL and to construct a model to predict this outcome. HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV RNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set (75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL were evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created. A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9–42.5) years; CD4 count was 147 (50–248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045–301,075) copies/mL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age 30 kg/m2 (OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1–5.1, p = 0.02), anemia (OR 1.70; 95% CI 1.40–2.10, p < 0.01), CD4 count >350 cells/mm3 (OR 3.9 vs. <100 cells/mm3; 95% CI 2.0–4.1, p < 0.01), total lymphocyte count >2000 cells/mm3 (OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3–2.3, p < 0.01), and no prior AIDS-defining illness (OR 1.8; 95% CI 1.5–2.3, p < 0.01). Receiver-operator characteristic (ROC) analysis yielded area under the curve of 0.70 (95% CI 0.67–0.72) among derivation patients and 0.69 (95% CI 0.65–0.74) among validation patients. A cut off score >25 yielded the sensitivity of 46.7%, specificity of 79.1%, positive predictive value of 67.7%, and negative predictive value of 61.2% for prediction of pre-treatment HIV RNA <100,000 copies/mL among derivation patients. A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC curve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.