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Rotavirus infection remains an important cause of morbidity and mortality in children. The introduction of vaccination programs in more than 100 countries has contributed to a decrease in hospitalizations and mortality. This study investigates the epidemiological impact of the rotavirus vaccine ROTAVAC® in the Palestinian Territories, the first country to switch from ROTARIX® to this new vaccine.Clinical surveillance data was collected fromchildren younger than 5attendingoutpatient clinics throughout Gaza withdiarrhea between 2015 and 2020. The incidence of all-cause diarrhea was assessed using an interrupted time-series approach. Rotavirus prevalence was determined at the Caritas Baby Hospital in the West Bank usingELISA on stool specimen of children younger than 5with diarrhea. Genotyping was performed on 325 randomly selected rotavirus-positive samples from January 2015 through December 2020 using multiplex PCR analysis.Average monthly diarrhea casesdropped by 16.7% annually fromintroduction of rotavirus vaccination in May 2016 to the beginning of the SARS-CoV-2 epidemic in March 2020 for a total of 53%. Case count declines were maintained afterthe switchto ROTAVAC® in October 2018. Rotavirus positivity in stool samples declined by 67.1% over the same period without change followingthe switch to ROTAVAC®. The distribution of predominant genotypes in rotavirus-positive stool samples changed from a pre-vaccination G1P [8] to G9P[8] and G12P[8] during the ROTARIX® period and G2P[4] after the introduction of ROTAVAC®.ROTAVAC® has shown epidemiological impact on par with ROTARIX® after its introduction to the national immunization schedule in the Palestinian Territories. A molecular genotype shift from a pre-vaccination predominance of G1P[8] to a current predominance of G2P[4] requires more long-term surveillance.

Environmental pathogen surveillance is a sensitive tool that can detect early-stage outbreaks, and it is being used to track poliovirus and other pathogens. However, interpretation of longitudinal environmental surveillance signals is difficult because the relationship between infection incidence and viral load in wastewater depends on time-varying shedding intensity. We developed a mathematical model of time-varying poliovirus shedding intensity consistent with expert opinion across a range of immunization states. Incorporating this shedding model into an infectious disease transmission model, we analysed quantitative, polymerase chain reaction data from seven sites during the 2013 Israeli poliovirus outbreak. Compared to a constant shedding model, our time-varying shedding model estimated a slower peak (four weeks later), with more of the population reached by a vaccination campaign before infection and a lower cumulative incidence. We also estimated the population shed virus for an average of 29 days (95% CI 28–31), longer than expert opinion had suggested for a population that was purported to have received three or more inactivated polio vaccine (IPV) doses. One explanation is that IPV may not substantially affect shedding duration. Using realistic models of time-varying shedding coupled with longitudinal environmental surveillance may improve our understanding of outbreak dynamics of poliovirus, SARS-CoV-2, or other pathogens.