Interplay of population mobility, healthcare resources, and spatiotemporal clustering

Background This study leverages Zhejiang Province’s HIV-confirmed positive blood donor database (2017–2024), integrating multidimensional data including demographic, serological, geospatial, and policy indicators to systematically analyze infection risk factors, screening marker characteristics, spatiotemporal distribution patterns, migration impacts, and the regulatory effects of healthcare resource allocation and government investment on donor HIV positivity. Methods 5,204,965 voluntary donors underwent nucleic acid/serological testing. Multivariate logistic regression, spatiotemporal scan statistics (SaTScan), estimated annual percentage change (EAPC) modeling, and correlation analyses were applied. Healthcare capacity was evaluated via principal component analysis (PCA) index; future trends projected using autoregressive integrated moving average (ARIMA). Results During April 2017 to December 2024, 449 HIV-positive donors were confirmed (8.63 per 100,000 donors), with significant risk factors including people moving in from high-prevalence areas (OR 1.56), male gender (OR 7.32), self-employed (OR 1.46), and non-regular donation status (OR 1.86), while older age (OR 0.97) and government employment (OR 0.49) served as protective factors. Among confirmed positives, 98.44% exhibited HIV Ag+Ab+NAT+ reactivity. There was significant provincial decline in positivity (EAPC = −12.41, p < 0.001) with March–July seasonal peak ( p = 0.017) and spatial cluster in northeastern Zhejiang during March 2018 (p < 0.001). The monthly HIV-positive rate among blood donors was significantly correlated with general population AIDS incidence (r = 0.445, p < 0.001). Age-gender disparities profiling revealed peak male positivity among 21-25-year-olds concentrated in northern Zhejiang, while females aged 46–50 showed the highest burden in eastern Zhejiang. Migration analysis indicated 31.02% (125/403) of HIV-positive donors originated from 10 high-incidence provinces from 2018 to 2024, and influx correlated with birthplace-specific positivity ( p < 0.001). Healthcare capacity ( p = 0.014) and government health expenditure ( p = 0.034) were both inversely correlated with donor positivity. ARIMA projections for 2025–2030 indicate oscillating declines in overall and male donors, while female rates stabilize. Conclusion Centralized testing and cross-regional deferral strategies have significantly reduced HIV positivity among Zhejiang’s donors. Persistent challenges include window-period transmission, low-viremia infections under antiretroviral therapy. Further reduction of residual transfusion risks requires integrated epidemiological surveillance, high-risk population interventions, and optimized healthcare resource allocation

Blood transfusion · China · Deferral · Disease · Health care · Population · Blood donation and transfusion practices · Hepatitis B Virus Studies · HIV/AIDS Research and Interventions · Epidemiology

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