Background

Given the waning of vaccine effectiveness and the shifting of the most dominant strains in the U.S., it is imperative to understand the association between vaccination coverage and Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) disease and mortality at the community levels and whether that association might vary according to the dominant SARS-CoV-2 strains in the U.S.

Methods

Generalized estimating equations were used to estimate associations between U.S. county-level cumulative vaccination rates and booster distribution and the daily change in county-wide Coronavirus 2019 disease (COVID-19) risks and mortality during Alpha, Delta and Omicron predominance. Models were adjusted for potential confounders at both county and state level. A 2-week lag and a 4-week lag were introduced to assess vaccination rate impact on incidence and mortality, respectively.

Results

Among 3,073 counties in 48 states, the average county population complete vaccination rate of all age groups was 50.79% as of March 11th, 2022. Each percentage increase in vaccination rates was associated with reduction of 4% (relative risk (RR) 0.9607 (95% confidence interval (CI): 0.9553, 0.9661)) and 3% (RR 0.9694 (95% CI: 0.9653, 0.9736)) in county-wide COVID-19 cases and mortality, respectively, when Alpha was the dominant variant. The associations between county-level vaccine rates and COVID-19 incidence diminished during the Delta and Omicron predominance. However, each percent increase in people receiving a booster shot was associated with reduction of 6% (RR 0.9356 (95% CI: 0.9235, 0.9479)) and 4% (RR 0.9595 (95% CI: 0.9431, 0.9761)) in COVID-19 incidence and mortality in the community, respectively, during the Omicron predominance.

Conclusions

Associations between complete vaccination rates and COVID-19 incidence and mortality appeared to vary with shifts in the dominant variant, perhaps due to variations in vaccine efficacy by variant or to waning vaccine immunity over time. Vaccine boosters were associated with notable protection against Omicron disease and mortality.

Abstract Background There is not much information on the differences in clinical, epidemiological and spatial characteristics of diarrhea due to V. cholerae and V. parahaemolyticus from non-coastal areas. We investigated the differences in clinical, epidemiological and spatial characteristics of the two Vibrio species in the urban slums of Kolkata, India. Methods The data of a cluster randomized cholera vaccine trial were used. We restricted the analysis to clusters assigned to placebo. Survival analysis of the time to the first episode was used to analyze risk factors for V. parahaemolyticus diarrhea or cholera. A spatial scan test was used to identify high risk areas for cholera and for V. parahaemolyticus diarrhea. Results In total, 54,519 people from the placebo clusters were assembled. The incidence of cholera (1.30/1000/year) was significantly higher than that of V. parahaemolyticus diarrhea (0.63/1000/year). Cholera incidence was inversely related to age, whereas the risk of V. parahaemolyticus diarrhea was age-independent. The seasonality of diarrhea due to the two Vibrio species was similar. Cholera was distinguished by a higher frequency of severe dehydration, and V. parahaemolyticus diarrhea was by abdominal pain. Hindus and those who live in household not using boiled or treated water were more likely to have V. parahaemolyticus diarrhea. Young age, low socioeconomic status, and living closer to a project healthcare facility were associated with an increased risk for cholera. The high risk area for cholera differed from the high risk area for V. parahaemolyticus diarrhea. Conclusion We report coexistence of the two vibrios in the slums of Kolkata. The two etiologies of diarrhea had a similar seasonality but had distinguishing clinical features. The risk factors and the high risk areas for the two diseases differ from one another suggesting different modes of transmission of these two pathogens.

The temporal switching of serotypes from serotype Ogawa to Inaba and back to Ogawa was identified in Vibrio cholerae O1, which was responsible for seasonal outbreaks of cholera in Dhaka during the period 2015 to 2018. In order to delineate the factors responsible for this serotype transition, we performed whole-genome sequencing (WGS) of V. cholerae O1 multidrug-resistant strains belonging to both the serotypes that were isolated during this interval where the emergence and subsequent reduction of the Inaba serotype occurred. The whole-genome-based phylogenetic analysis revealed clonal expansion of the Inaba isolates mainly responsible for the peaks of infection during 2016 to 2017 and that they might have evolved from the prevailing Ogawa strains in 2015 which coclustered with them. Furthermore, the wbeT gene in these Inaba serotype isolates was inactivated due to insertion of a transposable element at the same position signifying the clonal expansion. Also, V. cholerae isolates in the Inaba serotype dominant clade mainly contained classical ctxB allele and revealed differences in the genetic composition of Vibrioseventh pandemic island II (VSP-II) and the SXT integrative and conjugative element (SXT-ICE) compared to those of Ogawa serotype strains which remerged in 2018. The variable presence of phage-inducible chromosomal island-like element 1 (PLE1) was also noted in the isolates of the Inaba serotype dominant clade. The detailed genomic characterization of the sequenced isolates has shed light on the forces which could be responsible for the periodic changes in serotypes of V. cholerae and has also highlighted the need to analyze the mobilome in greater detail to obtain insights into the mechanisms behind serotype switching.IMPORTANCE The switching of serotype from Ogawa to Inaba and back to Ogawa has been observed temporally in Vibrio cholerae O1, which is responsible for endemic cholera in Bangladesh. The serospecificity is key for effective intervention and for preventing cholera, a deadly disease that continues to cause significant morbidity and mortality worldwide. In the present study, WGS of V. cholerae allowed us to better understand the factors associated with the serotype switching events observed during 2015 to 2018. Genomic data analysis of strains isolated during this interval highlighted variations in the genes ctxB, tcpA, and rtxA and also identified significant differences in the genetic content of the mobilome, which included key elements such as SXT ICE, VSP-II, and PLE. Our results indicate that selective forces such as antibiotic resistance and phage resistance might contribute to the clonal expansion and predominance of a particular V. cholerae serotype responsible for an outbreak.

Building on previous multicountry surveillance studies of typhoid and others salmonelloses such as the Diseases of the Most Impoverished program and the Typhoid Surveillance in Africa Project, several ongoing blood culture surveillance studies are generating important data about incidence, severity, transmission, and clinical features of invasive Salmonella infections in sub-Saharan Africa and South Asia. These studies are also characterizing drug resistance patterns in their respective study sites. Each study answers a different set of research questions and employs slightly different methodologies, and the geographies under surveillance differ in size, population density, physician practices, access to healthcare facilities, and access to microbiologically safe water and improved sanitation. These differences in part reflect the heterogeneity of the epidemiology of invasive salmonellosis globally, and thus enable generation of data that are useful to policymakers in decision-making for the introduction of typhoid conjugate vaccines (TCVs). Moreover, each study is evaluating the large-scale deployment of TCVs, and may ultimately be used to assess post-introduction vaccine impact. The data generated by these studies will also be used to refine global disease burden estimates. It is important to ensure that lessons learned from these studies not only inform vaccination policy, but also are incorporated into sustainable, low-cost, integrated vaccine-preventable disease surveillance systems.

BACKGROUND: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal sentinel surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS: The consortiums aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies. FUNDING: No specific funding was awarded for this meta-analysis. Coordinators were supported by fellowships from the European Union (ZAD received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council (DJI is supported by an NHMRC Investigator Grant [GNT1195210]).