Peer-reviewed article

Syphilis clustering among young pregnant women (18–35 years) in Kampala and Wakiso districts, Uganda

Rogers Nsubuga, Timothy R. Muwonge, Andrew Mujugira, Barbara Castelnuvo, Edith Nakku-Joloba et al. · 15 Jul 2026

Abstract

Introduction In Uganda, spatial distribution of syphilis varies by age, gender, and region. Identifying clusters (subsets of administrative subdivisions) with high syphilis prevalence could boost efforts to eliminate mother-to-child transmission of syphilis. We examined spatial variations and clustering of syphilis prevalence among pregnant young women aged 18–35 years in Central Uganda. Methods We analysed secondary data from a randomised trial that evaluated the effectiveness of three antenatal syphilis partner notification approaches (NCT02262390). This study analysed clustering of syphilis prevalence by administrative division in Kampala and Wakiso districts, using Moran's I tests and Local Indicator of Spatial Association (LISA). We used Kulldorff Spatial-Scan Poisson model to detect syphilis clustering and classified divisions into high- or low-prevalence (HP/LP) syphilis clusters based on 95% statistical significance. We estimated prevalence ratios for sociodemographic and bio-behavioural HIV risk factors associated with residence in HP divisions using modified Poisson regression. Results Of 422 women diagnosed with syphilis, 26 (6%) had HIV and syphilis. Median age was 26 years (IQR 24–29). Most (314, 74%) were in monogamous marriages, and half (50%) had attained secondary education. Syphilis prevalence clustering was negatively associated with residence in HP divisions among women in polygamous marriages [adjusted prevalence ratio (APR) = 0.64; 95%: 0.47–0.88], those with an unplanned pregnancy (APR = 0.78; 95% CI: 0.64–0.93), and who had HIV testing >3 months prior (APR = 0.83, 95% CI: 0.72–0.95). Syphilis prevalence was significantly higher in 3/12 clusters: Kasangati Town Council [Relative Risk (RR) = 2.79, p < 0.0001], Kawempe (RR = 2.52, p < 0.0001), and Nabweru (RR = 1.95, p = 0.0002), and lower in one cluster–Kyengera Town Council (RR = 0.12, p < 0.0001). Notably, no significant clustering was detected among women with HIV ( p > 0.05). Random patterns of syphilis prevalence were detected across all divisions (Moran's I = 0.08, p = 0.19). However, some neighbouring divisions had similar prevalence: Kawempe (1.06, p = 0.02) and Nabweru (0.54, p = 0.045). LISA analysis confirmed high syphilis prevalence in northern divisions (Kawempe and Nabweru; p = 0.01). By contrast, Central Region had neighbouring low and high prevalence divisions (Kawempe and Central; p = 0.001). Conclusion Syphilis prevalence was similar within neighbouring divisions, but highest in Kasangati Town Council and Kawempe. Integrating spatial analysis in routine surveillance will enable detection of clusters where interventions can be targeted to eliminate congenital syphilis.