At least one-third of the 34 million people living with human immunodeficiency virus (HIV) worldwide are infected with latent tuberculosis (TB). The aim of this study was to determine the rate of HIV infection in TB patients and its determinants in Wuxi City, China. TB patients attending health institutions (12 selected sites) for TB diagnosis and treatment were enrolled in this study. TB diagnosis, treatment and HIV testing were done according to the national guidelines. Blood samples were collected for anonymous HIV testing. Among the TB patients, the HIV prevalence was 13.66% (1493/10,926). Multivariate analysis showed that gender, age, education, marital status, per capita monthly income, patient residence, family size, distance from a health institution, knowledge of HIV-TB co-infection, and knowledge of HIV may be risk factors for HIV-TB co-infection (all: odds ratio > 1, p < 0.05). The prevalence of TB in those with HIV was higher among the study participants. Improving public awareness of HIV-TB co-infection, regularly screening and improving follow-up can reduce the occurrence of HIV-TB co-infection.
The COVID-19 pandemic had an unequal impact on the employment and earnings of different labourers, consequently affecting households’ per capita income and income inequality. Combining a multisector computable general equilibrium model of China with a micro-simulation approach, this study aims to analyse the unequal effect of the COVID-19 pandemic on China’s labour market and income inequality. The results confirm the unequal impact of the pandemic on the employment and earnings of different labourer types. Labourers who are female, live in urban areas, and have relatively low education levels would suffer greater losses in employment and earnings. The pandemic would reduce household per capita income by 8.75% for rural residents and 6.13% for urban residents. While the pandemic would have a larger negative impact on the employment and earnings of urban labourers, it would have a greater negative impact on the household per capita income of rural residents. Moreover, the per capita income of low-income households is more vulnerable to the pandemic, and the number of residents living below the poverty line would increase significantly. Thus, the pandemic would aggravate income inequality in China and threaten the livelihoods of poor families. This study could inform researchers exploring the distributional effect of the COVID-19 pandemic in developing countries.
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