Drug sales data for gastrointestinal infections surveillance: a systematic review up to 2025

Gastrointestinal infections are an important Public Health problem. International institutions suggest supporting traditional epidemiologic surveillance with syndromic surveillance, including the use of drug sales data monitoring. This review aims to investigate the usefulness of drug sales data as a tool for gastrointestinal infections surveillance by addressing the question “ could drug sales data be a complementary contribution to traditional epidemiological GI infections surveillance? ”. The bibliographic search was carried out in December 2025 using a specific string across 4 scientific literature databases (PubMed, Embase, CINAHL, Cochrane Library), according to PRISMA guidelines. Out of 5.905 publications screened, 15 met the inclusion criteria and were included in the review. The selected studies were published between 1983 and 2021, mostly conducted in Europe. Despite the wide variety of study designs, 73% ( n = 11) of the publications emphasized the usefulness and effectiveness of drug sales data for surveillance. In contrast, 20% ( n = 3) reported no utility, and 7% ( n = 1) found it to be less useful compared to other data sources. Many authors underlined the importance of considering the variables impacting the use and interpretation of drug sales data, and the importance of cooperation between healthcare providers to establish a virtuous surveillance system. In the present systematic review, most selected publications seem to define drug sales data as potentially useful complementary source of information for gastrointestinal infections detection. However, heterogeneity of studies, publication bias and limitations on search strategy do not allow for a definitive qualitative conclusion. The limited number of recent studies highlights the need for further research that also considers the analysis of behavioural factors. Moreover, to optimize the use of new drug sales data collection systems for gastroenteritis surveillance, the application of new computational methods appears promising. This systematic review was recorded in the register PROSPERO (ID number CRD42023492791).