Background
Respiratory syncytial virus (RSV) represents a substantial global health challenge, with a disproportionately high disease burden in low-income and middle-income countries. RSV exhibits seasonality in most areas globally, and a comprehensive understanding of within-country variations in RSV seasonality could help to define the timing of RSV immunisation programmes. This study focused on China, and aimed to describe the geographical distribution of RSV seasonality, identify distinct RSV transmission zones, and evaluate the potential suitability of a seasonal RSV prevention strategy.
Methods
We did a systematic analysis of RSV seasonality in China, with use of data on RSV activity extracted from a systematic review of studies published on Embase, MEDLINE, Web of Science, China National Knowledge Infrastructure, Wanfang Data, Chongqing VIP Information, and SinoMed, from database inception until May 5, 2023. We included studies of any design in China reporting at least 25 RSV cases, which aggregated RSV case number by calendar month or week at the province level, and with data covering at least 12 consecutive months before the year 2020 (prior to the COVID-19 pandemic). Studies that used only serology for RSV testing were excluded. We also included weekly data on RSV activity from open-access online databases of the Taiwan National Infection Disease Statistics System and Hong Kong Centre for Health Protection, applying the same eligiblity requirements. Across all datasets, we excluded data on RSV activity from Jan 1, 2020, onwards. We estimated RSV seasonal epidemic onset and duration using the annual average percentage (AAP) approach, and summarised seasonality at the provincial level. We used Pearson's partial correlation analysis to assess the correlation between RSV season duration and the latitude and longitude of the individual provinces. To define transmission zones, we used two independent approaches, an infant-passive-immunisation-driven approach (the moving interval approach, 6-month interval) and a data-driven approach (k-means), to identify groups of provinces with similar RSV seasonality. The systematic review was registered on PROSPERO, CRD42022376993.
Findings
A total of 157 studies were included along with the two online datasets, reporting data on 194 596 RSV cases over 442 study-years (covering the period from Jan 1, 1993 to Dec 31, 2019), from 52 sites in 23 provinces. Among 21 provinces with sufficient data (≥100 reported cases), the median duration of RSV seasonal epidemics was 4·6 months (IQR 4·1–5·4), with a significant latitudinal gradient (r=–0·69, p<0·0007), in that provinces on or near the Tropic of Cancer had the longest epidemic duration. We found no correlation between longitude and epidemic duration (r=–0·15, p=0·53). 15 (71%) of 21 provinces had RSV epidemics from November to March. 13 (62%) of 21 provinces had clear RSV seasonality (epidemic duration ≤5 months). The moving interval approach categorised the 21 provinces into four RSV transmission zones. The first zone, consisting of five provinces (Fujian, Guangdong, Hong Kong, Taiwan, and Yunnan), was assessed as unsuitable for seasonal RSV immunisation strategies; the other three zones were considered suitable for seasonal RSV immunisation strategies with the optimal start month varying between September (Hebei), October (Anhui, Chongqing, Henan, Hubei, Jiangsu, Shaanxi, Shandong, Shanghai, Sichuan, and Xinjiang), and November (Beijing, Gansu, Guizhou, Hunan, and Zhejiang). The k-means approach identified two RSV transmission zones, primarily differentiated by whether the province was on or near the Tropic of Cancer (Fujian, Guangdong, Hong Kong, Taiwan, Yunan, and Hunan) or not (the remaining 15 provinces).
Interpretation
Although substantial variations in RSV seasonality were observed across provinces of China, our study identified distinct transmission zones with shared RSV circulating patterns. These findings could have important implications for decision making on RSV passive immunisation strategy. Furthermore, the methodological framework in this study for defining RSV seasons and identifying RSV transmission zones is potentially applicable to other countries or regions.