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Introduction: Diarrhea is still a significant global public health problem. There are currently no systematic evaluation of the modeling areas and approaches to predict diarrheal illness outcomes. This paper reviews existing research efforts in predictive modeling of infectious diarrheal illness in pediatric populations. Methods: We conducted a systematic review via a PubMed search for the period 1990–2021. A comprehensive search query was developed through an iterative process and literature on predictive modeling of diarrhea was retrieved. The following filters were applied to the search results: human subjects, English language, and children (birth to 18 years). We carried out a narrative synthesis of the included publications. Results: Our literature search returned 2671 articles. After manual evaluation, 38 of these articles were included in this review. The most common research topic among the studies were disease forecasts 14 (36.8%), vaccine‐related predictions 9 (23.7%), and disease/pathogen detection 5 (13.2%). Majority of these studies were published between 2011 and 2020, 28 (73.7%). The most common technique used in the modeling was machine learning 12 (31.6%) with various algorithms used for the prediction tasks. With change in the landscape of diarrheal etiology after rotavirus vaccine introduction, many open areas (disease forecasts, disease detection, and strain dynamics) remain for pathogen‐specific predictive models among etiological agents that have emerged as important. Additionally, the outcomes of diarrheal illness remain under researched. We also observed lack of consistency in the reporting of results of prediction models despite the available guidelines highlighting the need for common data standards and adherence to guidelines on reporting of predictive models for biomedical research. Conclusions: Our review identified knowledge gaps and opportunities in predictive modeling for diarrheal illness, and limitations in existing attempts whilst advancing some precursory thoughts on how to address them, aiming to invigorate future research efforts in this sphere. [ABSTRACT FROM AUTHOR]

Background: Despite antibiotic prescription being recommended for dysentery and suspected cholera only, diarrhea still triggers unwarranted antibiotic prescription. We evaluated antibiotic-prescribing practices and their predictors among children aged 2–59 months in the Vaccine Impact on Diarrhea in Africa (VIDA) Study performed in The Gambia, Mali, and Kenya. Methods: VIDA was a prospective case-control study (May 2015–July 2018) among children presenting for care with moderate-to-severe diarrhea (MSD). We defined inappropriate antibiotic use as prescription or use of antibiotics when not indicated by World Health Organization (WHO) guidelines. We used logistic regression to assess factors associated with antibiotic prescription for MSD cases who had no indication for an antibiotic, at each site. Results: VIDA enrolled 4840 cases. Among 1757 (36.3%) who had no apparent indication for antibiotic treatment, 1358 (77.3%) were prescribed antibiotics. In The Gambia, children who presented with a cough (adjusted odds ratio [aOR]: 2.05; 95% confidence interval [95% CI]: 1.21–3.48) were more likely to be prescribed an antibiotic. In Mali, those who presented with dry mouth (aOR: 3.16; 95% CI: 1.02–9.73) were more likely to be prescribed antibiotics. In Kenya, those who presented with a cough (aOR: 2.18; 95% CI: 1.01–4.70), decreased skin turgor (aOR: 2.06; 95% CI: 1.02–4.16), and were very thirsty (aOR: 4.15; 95% CI: 1.78–9.68) were more likely to be prescribed antibiotics. Conclusions: Antibiotic prescription was associated with signs and symptoms inconsistent with WHO guidelines, suggesting the need for antibiotic stewardship and clinician awareness of diarrhea case-management recommendations in these settings. Inappropriate antibiotic prescribing for diarrheal diseases can promote antimicrobial resistance. In VIDA, unnecessary or incorrect antibiotics were prescribed for 77% of diarrhea and 41% of dysentery cases. Interventions are needed to promote judicious adherence to international guidelines in low-/middle-income countries. [ABSTRACT FROM AUTHOR]

Introduction: Healthcare delivery systems across the world have been shown to fall short of the ideals of being cost‐effective and meeting pre‐established standards of quality but the problem is more pronounced in Africa. Cloud computing emerges as a platform healthcare institutions could leverage to address these shortfalls. The aim of this study was to establish the extent of cloud computing adoption and its influence on health service delivery by public health facilities in Kisumu County. Methods: The study employed a cross‐sectional study design in one‐time data collection among facility in‐charges and health records officers from 57 public health facilities. The target population was 114 healthcare personnel and the sample size (n = 88) was computed using Yamane formula and drawn using stratified random sampling. Poisson regression was used to determine the influence of cloud computing adoption on the number of realized benefits to health service delivery. Results: Among 80 respondents, Cloud computing had been adopted by 42 (53%) while Software‐as‐a‐Service, Platform‐as‐a‐Service and Infrastructure‐as‐a‐Service implementations were at 100%, 0% and 5% among adopters, respectively. Overall, those who had adopted cloud computing realized a significantly higher number of benefits to health service delivery compared to those who had not (Incident‐rate ratio (IRR) =1.93, 95% confidence interval (95% CI) [1.36‐2.72]). A significantly higher number of benefits was realized by those who had implemented Infrastructure‐as‐a‐Service alongside Software‐as‐a‐Service (IRR = 2.22, 95% CI [1.15‐4.29]) and those who had implemented Software‐as‐a‐Service only (IRR = 1.89, 95% CI [1.33‐2.70]) compared to non‐adopters. We observed similar results in the stratified analysis looking at economic, operational, and functional benefits to health service delivery. Conclusion: Cloud computing resulted in improved health service delivery with these benefits still being realized irrespective of the service implementation model deployed. The findings buttress the need for healthcare institutions to adopt cloud computing and integrate it in their operations in order to improve health service delivery. [ABSTRACT FROM AUTHOR]

Background Although Shigella is an important cause of diarrhea in Kenyan children, robust research platforms capable of conducting incidence-based Shigella estimates and eventual Shigella- targeted clinical trials are needed to improve Shigella -related outcomes in children. Here, we describe characteristics of a disease surveillance platform whose goal is to support incidence and consequences of Shigella diarrhea as part of multicounty surveillance aimed at preparing sites and assembling expertise for future Shigella vaccine trials. Methods We mobilized our preexisting expertise in shigellosis, vaccinology, and diarrheal disease epidemiology, which we combined with our experience conducting population-based sampling, clinical trials with high (97%–98%) retention rates, and healthcare utilization surveys. We leveraged our established demographic surveillance system (DSS), our network of healthcare centers serving the DSS, and our laboratory facilities with staff experienced in performing microbiologic and molecular diagnostics to identify enteric infections. We joined these resources with an international network of sites with similar capabilities and infrastructure to form a cohesive scientific network, designated Enterics for Global Health (EFGH), with the aim of expanding and updating our knowledge of the epidemiology and adverse consequences of shigellosis and enriching local research and career development priorities. Conclusions Shigella surveillance data from this platform could help inform Shigella vaccine trials. [ABSTRACT FROM AUTHOR]

Background Comparative costs of public health interventions provide valuable data for decision making. However, the availability of comprehensive and context-specific costs is often limited. The Enterics for Global Health (EFGH) Shigella surveillance study—a facility-based diarrhea surveillance study across 7 countries—aims to generate evidence on health system and household costs associated with medically attended Shigella diarrhea in children. Methods EFGH working groups comprising representatives from each country (Bangladesh, Kenya, Malawi, Mali, Pakistan, Peru, and The Gambia) developed the study methods. Over a 24-month surveillance period, facility-based surveys will collect data on resource use for the medical treatment of an estimated 9800 children aged 6–35 months with diarrhea. Through these surveys, we will describe and quantify medical resources used in the treatment of diarrhea (eg, medication, supplies, and provider salaries), nonmedical resources (eg, travel costs to the facility), and the amount of caregiver time lost from work to care for their sick child. To assign costs to each identified resource, we will use a combination of caregiver interviews, national medical price lists, and databases from the World Health Organization and the International Labor Organization. Our primary outcome will be the estimated cost per inpatient and outpatient episode of medically attended Shigella diarrhea treatment across countries, levels of care, and illness severity. We will conduct sensitivity and scenario analysis to determine how unit costs vary across scenarios. Conclusions Results from this study will contribute to the existing body of literature on diarrhea costing and inform future policy decisions related to investments in preventive strategies for Shigella. [ABSTRACT FROM AUTHOR]

Background Rigorous data management systems and planning are essential to successful research projects, especially for large, multicountry consortium studies involving partnerships across multiple institutions. Here we describe the development and implementation of data management systems and procedures for the Enterics For Global Health (EFGH) Shigella surveillance study—a 7-country diarrhea surveillance study that will conduct facility-based surveillance concurrent with population-based enumeration and a health care utilization survey to estimate the incidence of Shigella- -associated diarrhea in children 6 to 35 months old. Methods The goals of EFGH data management are to utilize the knowledge and experience of consortium members to collect high-quality data and ensure equity in access and decision-making. During the planning phase before study initiation, a working group of representatives from each EFGH country site, the coordination team, and other partners met regularly to develop the data management systems for the study. Results This resulted in the Data Management Plan, which included selecting REDCap and SurveyCTO as the primary database systems. Consequently, we laid out procedures for data processing and storage, study monitoring and reporting, data quality control and assurance activities, and data access. The data management system and associated real-time visualizations allow for rapid data cleaning activities and progress monitoring and will enable quicker time to analysis. Conclusions Experiences from this study will contribute toward enriching the sparse landscape of data management methods publications and serve as a case study for future studies seeking to collect and manage data consistently and rigorously while maintaining equitable access to and control of data. [ABSTRACT FROM AUTHOR]

Background: While rotavirus causes severe diarrheal disease in children aged <5 years, data on other viral causes in sub-Saharan Africa are limited. Methods: In the Vaccine Impact on Diarrhea in Africa study (2015–2018), we analyzed stool from children aged 0–59 months with moderate-to-severe diarrhea (MSD) and without diarrhea (controls) in Kenya, Mali, and The Gambia using quantitative polymerase chain reaction. We derived the attributable fraction (AFe) based on the association between MSD and the pathogen, accounting for other pathogens, site, and age. A pathogen was attributable if the AFe was ≥0.5. The severity of attributable MSD was defined by a modified Vesikari score (mVS). Monthly cases were plotted against temperature and rainfall to assess seasonality. Results: Among 4840 MSD cases, proportions attributed to rotavirus, adenovirus 40/41, astrovirus, and sapovirus were 12.6%, 2.7%, 2.9%, and 1.9%, respectively. Attributable rotavirus, adenovirus 40/41, and astrovirus MSD cases occurred at all sites, with mVS of 11, 10, and 7, respectively. MSD cases attributable to sapovirus occurred in Kenya, with mVS of 9. Astrovirus and adenovirus 40/41 peaked during the rainy season in The Gambia, while rotavirus peaked during the dry season in Mali and The Gambia. Conclusions: In sub-Saharan Africa, rotavirus was the most common cause of MSD; adenovirus 40/41, astrovirus, and sapovirus contributed to a lesser extent among children aged <5 years. Rotavirus- and adenovirus 40/41-attributable MSD were most severe. Seasonality varied by pathogen and location. Efforts to increase the coverage of rotavirus vaccines and to improve prevention and treatment for childhood diarrhea should continue. Among children <5 years, rotavirus, adenovirus 40/41, and astrovirus cause moderate to severe diarrhea (MSD) in Kenya, Mali, and The Gambia, and sapovirus causes MSD in Kenya. Rotavirus and adenovirus 40/41 MSD have the highest severity. [ABSTRACT FROM AUTHOR]

Background: To address knowledge gaps regarding diarrheagenic Escherichia coli (DEC) in Africa, we assessed the clinical and epidemiological features of enteroaggregative E. coli (EAEC), enteropathogenic E. coli (EPEC), and Shiga toxin–producing E. coli (STEC) positive children with moderate-to-severe diarrhea (MSD) in Mali, The Gambia, and Kenya. Methods: Between May 2015 and July 2018, children aged 0–59 months with medically attended MSD and matched controls without diarrhea were enrolled. Stools were tested conventionally using culture and multiplex polymerase chain reaction (PCR), and by quantitative PCR (qPCR). We assessed DEC detection by site, age, clinical characteristics, and enteric coinfection. Results: Among 4840 children with MSD and 6213 matched controls enrolled, 4836 cases and 1 control per case were tested using qPCR. Of the DEC detected with TAC, 61.1% were EAEC, 25.3% atypical EPEC (aEPEC), 22.4% typical EPEC (tEPEC), and 7.2% STEC. Detection was higher in controls than in MSD cases for EAEC (63.9% vs 58.3%, P <.01), aEPEC (27.3% vs 23.3%, P <.01), and STEC (9.3% vs 5.1%, P <.01). EAEC and tEPEC were more frequent in children aged <23 months, aEPEC was similar across age strata, and STEC increased with age. No association between nutritional status at follow-up and DEC pathotypes was found. DEC coinfection with Shigella/enteroinvasive E. coli was more common among cases (P <.01). Conclusions: No significant association was detected between EAEC, tEPEC, aEPEC, or STEC and MSD using either conventional assay or TAC. Genomic analysis may provide a better definition of the virulence factors associated with diarrheal disease. [ABSTRACT FROM AUTHOR]

Background: To address a paucity of data from sub-Saharan Africa, we examined the prevalence, severity, and seasonality of norovirus genogroup II (NVII) among children <5 years old in The Gambia, Kenya, and Mali following rotavirus vaccine introduction. Methods: Population-based surveillance was conducted to capture medically-attended moderate-to-severe diarrhea (MSD) cases, defined as a child 0–59 months old passing ≥3 loose stools in a 24-hour period with ≥1 of the following: sunken eyes, poor skin turgor, dysentery, intravenous rehydration, or hospitalization within 7 days of diarrhea onset. Diarrhea-free matched controls randomly selected from a censused population were enrolled at home. Stools from cases and controls were tested for enteropathogens, including norovirus and rotavirus, by TaqMan quantitative polymerase chain reaction (PCR) and conventional reverse transcription PCR. We used multiple logistic regression to derive adjusted attributable fractions (AFe) for each pathogen causing MSD, which takes into consideration the prevalence in both cases and controls, for each site and age. A pathogen was considered etiologic if AFe was ≥0.5. In further analyses focusing on the predominant NVII strains, we compared rotavirus and NVII severity using a 20-point modified Vesikari score and examined seasonal fluctuations. Results: From May 2015 to July 2018, we enrolled 4840 MSD cases and 6213 controls. NVI was attributed to only 1 MSD episode. NVII was attributed to 185 (3.8%) of all MSD episodes and was the sole attributable pathogen in 139 (2.9%); peaking (36.0%) at age 6–8 months with majority (61.2%) aged 6–11 months. MSD cases whose episodes were attributed to NVII alone compared with rotavirus alone were younger (median age, 8 vs 12 months, P <.0001) and had less severe illness (median Vesikari severity score, 9 vs 11, P =.0003) but equally likely to be dehydrated. NVII occurred year-round at all study sites. Conclusions: Infants aged 6–11 months bear the greatest burden of norovirus disease, with NVII predominating. An early infant vaccine schedule and rigorous adherence to guidelines recommended for management of dehydrating diarrhea may offer substantial benefit in these African settings. Norovirus genogroup II was the attributed etiology for 3% of all moderate-to-severe diarrhea (MSD) cases among children <5 years old in The Gambia, Mali, and Kenya post-rotavirus vaccine introduction; the highest disease burden concentrated in children 6–11 months old. [ABSTRACT FROM AUTHOR]

Background: The magnitude of pediatric enteric pathogen exposures in low-income settings necessitates substantive water and sanitation interventions, including animal feces management. We assessed associations between pediatric enteric pathogen detection and survey-based water, sanitation, and animal characteristics within the Vaccine Impact on Diarrhea in Africa case-control study. Methods: In The Gambia, Kenya, and Mali, we assessed enteric pathogens in stool of children aged <5 years with moderate-to-severe diarrhea and their matched controls (diarrhea-free in prior 7 days) via the TaqMan Array Card and surveyed caregivers about household drinking water and sanitation conditions and animals living in the compound. Risk ratios (RRs) and 95% confidence intervals (CIs) were calculated using modified Poisson regression models, stratified for cases and controls and adjusted for age, sex, site, and demographics. Results: Bacterial (cases, 93%; controls, 72%), viral (63%, 56%), and protozoal (50%, 38%) pathogens were commonly detected (cycle threshold <35) in the 4840 cases and 6213 controls. In cases, unimproved sanitation (RR, 1.56; 95% CI, 1.12–2.17), as well as cows (RR, 1.61; 95% CI, 1.16–2.24) and sheep (RR, 1.48; 95% CI, 1.11–1.96) living in the compound, were associated with Shiga toxin–producing Escherichia coli. In controls, fowl (RR, 1.30; 95% CI, 1.15–1.47) were associated with Campylobacter spp. In controls, surface water sources were associated with Cryptosporidium spp., Shigella spp., heat-stable toxin-producing enterotoxigenic E. coli, and Giardia spp. Conclusions: Findings underscore the importance of enteric pathogen exposure risks from animals alongside more broadly recognized water and sanitation risk factors in children. We assessed survey-based water, sanitation, and animal factors associated with enteric pathogens in cases of moderate to severe diarrhea and controls. Animals, cows and sheep (cases) and fowl (controls), were associated with bacterial carriage; surface water was associated with bacteria and protozoa in controls. [ABSTRACT FROM AUTHOR]

Background: Kenya introduced the monovalent G1P [8] Rotarix® vaccine into the infant immunization schedule in July 2014. We examined trends in rotavirus group A (RVA) genotype distribution pre- (January 2010-June 2014) and post- (July 2014-December 2018) RVA vaccine introduction.Methods: Stool samples were collected from children aged < 13 years from four surveillance sites across Kenya: Kilifi County Hospital, Tabitha Clinic Nairobi, Lwak Mission Hospital, and Siaya County Referral Hospital (children aged < 5 years only). Samples were screened for RVA using enzyme linked immunosorbent assay (ELISA) and VP7 and VP4 genes sequenced to infer genotypes.Results: We genotyped 614 samples in pre-vaccine and 261 in post-vaccine introduction periods. During the pre-vaccine introduction period, the most frequent RVA genotypes were G1P [8] (45.8%), G8P [4] (15.8%), G9P [8] (13.2%), G2P [4] (7.0%) and G3P [6] (3.1%). In the post-vaccine introduction period, the most frequent genotypes were G1P [8] (52.1%), G2P [4] (20.7%) and G3P [8] (16.1%). Predominant genotypes varied by year and site in both pre and post-vaccine periods. Temporal genotype patterns showed an increase in prevalence of vaccine heterotypic genotypes, such as the commonly DS-1-like G2P [4] (7.0 to 20.7%, P < .001) and G3P [8] (1.3 to 16.1%, P < .001) genotypes in the post-vaccine introduction period. Additionally, we observed a decline in prevalence of genotypes G8P [4] (15.8 to 0.4%, P < .001) and G9P [8] (13.2 to 5.4%, P < .001) in the post-vaccine introduction period. Phylogenetic analysis of genotype G1P [8], revealed circulation of strains of lineages G1-I, G1-II and P [8]-1, P [8]-III and P [8]-IV. Considerable genetic diversity was observed between the pre and post-vaccine strains, evidenced by distinct clusters.Conclusion: Genotype prevalence varied from before to after vaccine introduction. Such observations emphasize the need for long-term surveillance to monitor vaccine impact. These changes may represent natural secular variation or possible immuno-epidemiological changes arising from the introduction of the vaccine. Full genome sequencing could provide insights into post-vaccine evolutionary pressures and antigenic diversity. [ABSTRACT FROM AUTHOR]

Background Monovalent rotavirus vaccine, Rotarix (GlaxoSmithKline), was introduced in Kenya in July 2014 and is recommended to infants as oral doses at ages 6 and 10 weeks. A multisite study was established in 2 population-based surveillance sites to evaluate vaccine impact on the incidence of rotavirus-associated hospitalizations (RVHs). Methods Hospital-based surveillance was conducted from January 2010 to June 2017 for acute diarrhea hospitalizations among children aged <5 years in 2 health facilities in Kenya. A controlled interrupted time-series analysis was undertaken to compare RVH pre– and post–vaccine introduction using rotavirus-negative cases as a control series. The change in incidence post–vaccine introduction was estimated from a negative binomial model that adjusted for secular trend, seasonality, and multiple health worker industrial actions (strikes). Results Between January 2010 and June 2017 there were 1513 and 1652 diarrhea hospitalizations in Kilifi and Siaya; among those tested for rotavirus, 28% (315/1142) and 23% (197/877) were positive, respectively. There was a 57% (95% confidence interval [CI], 8–80%) reduction in RVHs observed in the first year post–vaccine introduction in Kilifi and a 59% (95% CI, 20–79%) reduction in Siaya. In the second year, RVHs decreased further at both sites, 80% (95% CI, 46–93%) reduction in Kilifi and 82% reduction in Siaya (95% CI. 61–92%); this reduction was sustained at both sites into the third year. Conclusions A substantial reduction in RVHs and all-cause diarrhea was observed in 2 demographic surveillance sites in Kenya within 3 years of vaccine introduction. [ABSTRACT FROM AUTHOR]

Background Rotavirus remains a leading cause of pediatric diarrheal illness and death worldwide. Data on rotavirus vaccine effectiveness in sub-Saharan Africa are limited. Kenya introduced monovalent rotavirus vaccine (RV1) in July 2014. We assessed RV1 effectiveness against rotavirus-associated hospitalization in Kenyan children. Methods Between July 2014 and December 2017, we conducted surveillance for acute gastroenteritis (AGE) in 3 Kenyan hospitals. From children age-eligible for ≥1 RV1 dose, with stool tested for rotavirus and confirmed vaccination history we compared RV1 coverage among rotavirus positive (cases) vs rotavirus negative (controls) using multivariable logistic regression and calculated effectiveness based on adjusted odds ratio. Results Among 677 eligible children, 110 (16%) were rotavirus positive. Vaccination data were available for 91 (83%) cases; 51 (56%) had 2 RV1 doses and 33 (36%) 0 doses. Among 567 controls, 418 (74%) had vaccination data; 308 (74%) had 2 doses and 69 (16%) 0 doses. Overall 2-dose effectiveness was 64% (95% confidence interval [CI], 35%–80%); effectiveness was 67% (95% CI, 30%–84%) for children aged <12 months and 72% (95% CI, 10%–91%) for children aged ≥12 months. Significant effectiveness was seen in children with normal weight for age, length/height for age and weight for length/height; however, no protection was found among underweight, stunted, or wasted children. Conclusions RV1 in the Kenyan immunization program provides significant protection against rotavirus-associated hospitalization which persisted beyond infancy. Malnutrition appears to diminish vaccine effectiveness. Efforts to improve rotavirus uptake and nutritional status are important to maximize vaccine benefit. [ABSTRACT FROM AUTHOR]

Background: Rotavirus vaccine was introduced in Kenya immunization program in July 2014. Pre-vaccine disease burden estimates are important for assessing vaccine impact.Methods: Children with acute gastroenteritis (AGE) (≥3 loose stools and/or ≥ 1 episode of unexplained vomiting followed by loose stool within a 24-h period), hospitalized in Siaya County Referral Hospital (SCRH) from January 2010 through December 2013 were enrolled. Stool specimens were tested for rotavirus (RV) using an enzyme immunoassay (EIA). Hospitalization rates were calculated using person-years of observation (PYO) from the Health Demographic Surveillance System (HDSS) as a denominator, while adjusting for healthcare utilization at household level and proportion of stool specimen collected from patients who met the case definition at the surveillance hospital. Mortality rates were calculated using PYO as the denominator and number of deaths estimated using total deaths in the HDSS, proportion of deaths attributed to diarrhoea by verbal autopsy (VA) and percent positive for rotavirus AGE (RVAGE) hospitalizations.Results: Of 7760 all-cause hospitalizations among children < 5 years of age, 3793 (49%) were included in the analysis. Of these, 21% (805) had AGE; RV was detected in 143 (26%) of 541 stools tested. Among children < 5 years, the estimated hospitalization rates per 100,000 PYO for AGE and RVAGE were 2413 and 429, respectively. Mortality rate associated with AGE and RVAGE were 176 and 45 per 100,000 PYO, respectively.Conclusion: AGE and RVAGE caused substantial health care burden (hospitalizations and deaths) before rotavirus vaccine introduction in Kenya. [ABSTRACT FROM AUTHOR]

Background: Kenya introduced the monovalent G1P [8] Rotarix® vaccine into the infant immunization schedule in July 2014. We examined trends in rotavirus group A (RVA) genotype distribution pre- (January 2010–June 2014) and post- (July 2014–December 2018) RVA vaccine introduction. Methods: Stool samples were collected from children aged < 13 years from four surveillance sites across Kenya: Kilifi County Hospital, Tabitha Clinic Nairobi, Lwak Mission Hospital, and Siaya County Referral Hospital (children aged < 5 years only). Samples were screened for RVA using enzyme linked immunosorbent assay (ELISA) and VP7 and VP4 genes sequenced to infer genotypes. Results: We genotyped 614 samples in pre-vaccine and 261 in post-vaccine introduction periods. During the pre-vaccine introduction period, the most frequent RVA genotypes were G1P [8] (45.8%), G8P [4] (15.8%), G9P [8] (13.2%), G2P [4] (7.0%) and G3P [6] (3.1%). In the post-vaccine introduction period, the most frequent genotypes were G1P [8] (52.1%), G2P [4] (20.7%) and G3P [8] (16.1%). Predominant genotypes varied by year and site in both pre and post-vaccine periods. Temporal genotype patterns showed an increase in prevalence of vaccine heterotypic genotypes, such as the commonly DS-1-like G2P [4] (7.0 to 20.7%, P <.001) and G3P [8] (1.3 to 16.1%, P <.001) genotypes in the post-vaccine introduction period. Additionally, we observed a decline in prevalence of genotypes G8P [4] (15.8 to 0.4%, P <.001) and G9P [8] (13.2 to 5.4%, P <.001) in the post-vaccine introduction period. Phylogenetic analysis of genotype G1P [8], revealed circulation of strains of lineages G1-I, G1-II and P [8]-1, P [8]-III and P [8]-IV. Considerable genetic diversity was observed between the pre and post-vaccine strains, evidenced by distinct clusters. Conclusion: Genotype prevalence varied from before to after vaccine introduction. Such observations emphasize the need for long-term surveillance to monitor vaccine impact. These changes may represent natural secular variation or possible immuno-epidemiological changes arising from the introduction of the vaccine. Full genome sequencing could provide insights into post-vaccine evolutionary pressures and antigenic diversity. [ABSTRACT FROM AUTHOR]