BACKGROUND: There are very few studies in Saudi Arabia on stigmatization and discrimination against people living with HIV/AIDS (PLWHA), a critical step for the prevention and control of HIV. The aim of this study was to assess the level of stigmatization and discrimination against PLWHA by healthcare workers (HCWs) as well as their knowledge, attitude, and practices (KAP). MATERIALS AND METHODS: This cross-sectional study included 182 HCWs at primary healthcare centers in Medina, Saudi Arabia. The validated short version of the Healthcare Provider HIV/AIDS Stigma Scale and the AIDS Attitude Scale were used in this research. Student’s t-test and analysis of variance (ANOVA) were used to assess the differences in the mean knowledge, attitudes, and practices KAP scores by various sociodemographic factors. Multiple linear regression analysis was used to determine factors associated with KAP scores. RESULTS: Most participants were males (58.2%) and aged more than 30 years (60.4%). The tendency to stigmatizing behavior was present in 24.2%–68.17% of the participants, and discriminatory practice was present in 11.5%–50% of the participants. In multiple linear regression analysis, factors that independently predicted the knowledge score were being a doctor compared to nurses (P < 0.001), receiving in-service training for PLWHA (P < 0.001), and male gender (P = 0.002). Attitude was predicted by being female (P = 0.008) and a doctor (P = 0.005). Practice was predicted by the knowledge score (P < 0.001) and being married (P = 0.035). CONCLUSION: This study found that stigmatization and discrimination were less prevalent in HCWs who had good HIV-related knowledge and had received in-service training for PLWHA. The results highlight the significance of continuing education and training opportunities for HCWs to provide effective and appropriate treatment to PLWHA.

Demand for influenza vaccine rose as countries prepared for the second COVID-19 wave over the winter months of 2020-2021. High coverage of the influenza vaccine can significantly reduce morbidity and mortality of the burden of influenza. Natural influenza infection creates short-term non-specific immunity against respiratory viruses (virus interference). We model two viral diseases, both of the SEIR type, to investigate whether the influenza vaccine increases the combined disease burden of influenza and COVID-19 in a dual outbreak. We show that the combined disease burden's behavior depends on virus interference factors and the proportion of the population vaccinated against influenza. Our results indicate that influenza vaccination only lowers the overall disease burden when net virus interference is relatively low.

SARS-CoV-2 has caused severe respiratory illnesses and deaths since late 2019 and spreads globally. While asymptomatic cases play a crucial role in transmitting COVID-19, they do not contribute to the observed prevalence, which drives behavior change during the pandemic. This study aims to identify the effect of the proportion of asymptomatic infections on the magnitude of an epidemic under behavior change scenarios by developing a compartmental mathematical model. In this interest, we discuss three different behavior change cases separately: constant behavior change, instantaneous behavior change response to the disease’s perceived prevalence, and piecewise constant behavior change response to government policies. Our results imply that the proportion of asymptomatic infections which maximizes the spread of the epidemic depends on the nature of the dominant force driving behavior changes.

We present a nonautonomous compartmental model that incorporates vaccination and accounts for the seasonal transmission of typhoid fever. The dynamics of the system are governed by the basic reproductive number R0. This demonstrates the global stability of the disease-free solution if R0<1. On the contrary, if R0>1, the disease persists and positive periodic solutions exist. Numerical simulations validate our theoretical findings. To accurately fit typhoid fever data in Taiwan from 2008 to 2023, we use the model and estimate its parameters using Latin hypercube sampling and least squares techniques. A sensitivity analysis reveals the significant influence of parameters such as infection rates on the reproduction number. Increasing vaccination coverage, despite challenges in developing countries, reduces typhoid cases. Accessible and highly effective vaccines play a critical role in suppressing the epidemic, outweighing concerns about the efficacy of the vaccine. Investigating possible parameter changes in Taiwan highlights the importance of monitoring and managing transmission rates to prevent recurring annual epidemics.

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