A fifteen-year epidemiological surveillance study investigating other infectious diarrhea in Kunming, China, reveals that reported infections increased significantly between 2011 and 2025, accompanied by broadening demographic involvement, increasing pathogen diversity, and synchronized regional epidemic timing. Published in Discover Public Health, the observational analysis examined 152,090 cases logged in the China Information System for Disease Control and Prevention, documenting an overall average annual incidence of 134.3 cases per 100,000 population across the municipality. Over the surveillance period, municipal incidence climbed from 62.7 per 100,000 population in 2011 to 273.2 per 100,000 population in 2025, corresponding to an average annual percent change of 11.2 percent that accelerated notably after 2023.
In China’s classification-based disease surveillance architecture, cholera, bacterial dysentery, amoebic dysentery, and typhoid or paratyphoid fever receive individual monitoring, while remaining infectious diarrheal presentations are categorized collectively as other infectious diarrhea, a Category C notifiable condition subject to routine reporting within twenty-four hours. Kunming, the capital of Yunnan Province, sits on the Yunnan-Guizhou Plateau at an average elevation of approximately 1,890 meters and covers an area of roughly 21,000 square kilometers with a resident population exceeding 8.6 million people across fourteen county-level administrative divisions. Because the city links southwest China with the Greater Mekong Subregion, regional population movement, rapid urban expansion, and a subtropical plateau climate create complex, place-specific environments for the circulation and transmission of diverse enteric pathogens.
To evaluate the long-term multidimensional trajectory of other infectious diarrhea, researchers applied descriptive epidemiological methods alongside specialized analytical time-series tools. Seasonal-trend decomposition using Loess was utilized to dissect raw incidence records into baseline trend trajectories, cyclical seasonal fluctuations, and irregular residual components, while continuous wavelet transform identified oscillatory cycles across multiple temporal scales. Pathogen diversity across surveillance years and demographic tiers was assessed using the Shannon-Wiener diversity index, which incorporates both richness and evenness, and sex-specific incidence rates were compared using Poisson regression models. Long-term incidence trends across demographic groups and overall temporal phases were quantified using Joinpoint regression models to locate statistically significant inflection points.
Joinpoint regression identified distinct temporal phases in incidence intensity across the fifteen-year period. From 2011 to 2019, incidence maintained a steady upward course with an annual percent change of 16.1 percent before reaching an initial joinpoint in 2019. This was followed by a statistically non-significant decline between 2019 and 2022, characterized by an annual percent change of negative 18.5 percent during a period marked by non-pharmaceutical interventions associated with the coronavirus pandemic. After 2022, a second joinpoint emerged as incidence rebounded sharply into an accelerated upward trajectory with an annual percent change of 34.9 percent. Seasonal-trend decomposition indicated that the annual seasonal-to-trend ratio increased from a historical median of approximately 1.5 to above 3.0 after 2023, while wavelet analysis detected enhanced multi-scale oscillations across annual, sub-annual, and interannual scales that peaked in intensity in 2025.
Surveillance data revealed an established bimodal seasonal structure throughout the fifteen-year timeline, defined by a primary winter peak between December and January and a secondary spring surge from March through April. However, both the magnitude and duration of these seasonal peaks expanded substantially after 2023, surpassing historical ten-year baselines. The overall reported cases included a slight male predominance, with 82,903 male cases representing 53.5 percent of total reports, corresponding to a male-to-female ratio of 1.2 to 1 and a significantly higher mean annual incidence among males of 148.1 per 100,000 compared to 129.5 per 100,000 among females, yielding an incidence rate ratio of 1.144.
Although children aged zero to four years constituted the largest single demographic share of reported cases at 67.0 percent, or 101,899 of the 152,090 total infections, Joinpoint models documented statistically significant upward incidence trends across all age categories. Occupational distribution aligned closely with age structures, with community children cared for at home prior to kindergarten representing 63.1 percent of cases, followed by students at 7.7 percent and housewives or unemployed individuals at 6.2 percent. Joinpoint regression demonstrated pronounced annual percentage increases among preschool children attending nurseries or kindergartens at an average annual percent change of 21.3 percent, housewives and unemployed individuals at 11.3 percent, and farmers at 8.0 percent.
Among 38,902 laboratory-confirmed cases identified through standardized pathogen culture, antigen assays, microscopy, or nucleic acid testing, viral infections dominated, making up 99.2 percent of confirmed infections. Rotavirus was the most frequently identified agent at 69.7 percent of confirmed cases, followed by norovirus at 26.7 percent and adenovirus at 2.8 percent, whereas bacterial infections accounted for only 0.7 percent and fungal or parasitic diagnoses represented 0.1 percent. Although rotavirus, norovirus, and adenovirus infections were primarily concentrated in children aged zero to four years—who represented 89.1 percent, 72.0 percent, and 88.2 percent of their respective pathogen totals—older age cohorts, particularly individuals aged fifty and above, exhibited greater pathogen diversity and higher relative proportions of bacterial, fungal, and parasitic infections.
The annual Shannon-Wiener diversity index escalated in a stepwise pattern after 2020, rising from a baseline mean of approximately 0.1 between 2011 and 2015 to exceeding 0.8 during the 2023 to 2025 interval. This transition reflected a clear shift from historic single-pathogen dominance toward a multi-pathogen distribution, with individual pathogens increasingly detected beyond their traditional demographic ranges. Norovirus incidence expanded notably into older groups, including adolescents aged ten to fourteen years and elderly individuals over eighty-five years, with incidence among children aged five to nine climbing from under 10 to over 90 per 100,000 population between the 2019–2022 baseline and 2023–2025. Concurrently, rotavirus infections increasingly emerged among non-traditional adult cohorts, particularly adults aged thirty to thirty-nine years and individuals older than seventy years after 2022.
Geographic analysis showed that other infectious diarrhea occurred across all administrative jurisdictions in Kunming, but incidence varied widely by locality. Anning sustained the highest municipal average annual incidence at 244.5 per 100,000 population and reached 408.1 per 100,000 population in 2025, whereas the northern, geographically separated district of Dongchuan recorded the lowest average annual rate at 70.4 per 100,000 population. Spatiotemporal ridge plot analyses indicated that prior to 2022, regional epidemic waves were asynchronous; during the 2017 to 2018 cycle, Type A central districts peaked first, while Type B districts followed approximately twelve months later in 2019. After 2022, however, this regional asynchrony diminished, transitioning by 2024 and 2025 into synchronized surges across most districts, except in Dongchuan.
The authors contextualized these epidemiological transitions as a multidimensional expansion potentially shaped by interconnected host, pathogen, and environmental factors. Broadened population susceptibility, population aging, changes in immune landscapes, non-pharmaceutical interventions during the COVID-19 pandemic, and rotavirus vaccination coverage may interact with pathogen competition and ecological niche shifts, while rapid urbanization and regional mobility alter transmission dynamics. Localized urban functions also demonstrated distinct influences, as seen in Anning’s stable high rates among dense industrial networks and Chenggong’s recurrent university-linked outbreaks. The authors noted several observational limitations: the dataset relied on passive surveillance from the notifiable reporting system, laboratory testing did not encompass all clinically reported cases, and diagnostic testing practices or pathogen identification capacities may have varied across institutions and years, precluding direct individual-level causal determinations.
Subject of Research: Spatiotemporal dynamics and pathogen spectrum of other infectious diarrhea in Kunming from 2011 to 2025
Article Title: Spatiotemporal dynamics and pathogen spectrum of other infectious diarrhea in Kunming, China from 2011 to 2025
Article References: Zhang, X., Zhang, X., Zhou, Y., Jing, X., Mao, Z., Zhang, L., Shui, T., & Yan, X. (2026). Spatiotemporal dynamics and pathogen spectrum of other infectious diarrhea in Kunming, China from 2011 to 2025. Discover Public Health, 23(1), Article 1754. https://doi.org/10.1186/s12982-026-03177-2
Image Credits: AI Generated
DOI: 10.1186/s12982-026-03177-2
Keywords: infectious diarrhea, epidemiology, Kunming, rotavirus, norovirus, disease surveillance, public health, spatiotemporal analysis, Spatiotemporal, dynamics, pathogen, spectrum
Tags: disease surveillancedynamicsEpidemiologyinfectious diarrheaKunmingnoroviruspathogenPublic Healthrotavirusspatiotemporalspatiotemporal analysisspectrum
