<p>Due to relative poverty, China’s rural areas face challenges in preventing and controlling infectious diseases. Close contact data are essential for understanding the spread of infections; however, there is currently a lack of quantitative analysis and assessment of infection risk associated with human behavior in rural areas. This study addresses the challenges rural areas face in controlling respiratory infectious diseases due to underdeveloped economies and vulnerable populations. It focuses on close contact as the primary transmission route and bridges the gap in real indoor close contact behavior data, providing a scientific basis for effective prevention and control. This study developed a model based on real indoor close contact behaviors to simulate infectious disease spread and quantify viral exposure and infection risk in rural China. Effectiveness of non-pharmaceutical interventions in high-risk indoor environments was quantified. In rural areas with a 1% disease prevalence, the highest hourly infection risk was 0.28% in restaurants, followed by clinics and classrooms. Close contact risks in rural homes, offices, clinics, and classrooms were up to 1.6 times higher than in urban areas. These risks could be reduced below 0.1% with targeted interventions: (1) in restaurants, set air change rate to 5.8 ACH, with 1.5-m seat spacing and mandatory mask-wearing during non-meal times; (2) in classrooms, set air change rate to 14 ACH, with mask-wearing and online/offline blended learning ensuring 1.5-m spacing between desks for offline students; (3) in clinics, set air change rate to 8.8 ACH, encourage telemedicine for half the population, and require mask-wearing. The interventions reduce infection risk by 69.9% in restaurants, 67.8% in classrooms, and 77.4% in clinics. This study highlights the high infection risk in rural restaurants, classrooms, homes, and clinics, and suggests targeted measures to support effective epidemic prevention in these indoor environments.</p>