https://orcid.org/0000-0002-8659-5943
Figures
Abstract
Introduction
Shigella is a leading cause of diarrhea worldwide. While the burden of Shigella has been shown to be highest in Africa and Asia, recent studies have also shown considerable burden in the Americas. With several pediatric Shigella vaccines in clinical development, policymakers in the region will eventually consider whether a Shigella vaccine is appropriate for their setting.
Methods
We conducted a systematic review and meta-analyses to summarize the burden (characterized by prevalence, incidence, and attributable fraction estimates) of Shigella diarrhea among children under 72 months in the Americas, excluding the U.S., Canada, and Greenland. We searched published and pre-print articles available in six databases from January 1, 2000 through July 18, 2024. Random effects meta-analyses were conducted for subgroups of interest when relevant data from at least two studies were present.
Results
This review included 34 studies conducted across 14 countries in the region. Prevalence was most frequently reported, followed by incidence, then attributable fraction. Across all prevalence studies that used a culture detection method (n = 23), the pooled prevalence of Shigella among diarrhea cases was 3.1% (95% CI: 1.6- 5.8). The pooled prevalence among 7 studies that used PCR/qPCR detection methods was 16.5% (95% CI: 11.1-24.0). Among culture-based results, the pooled prevalence estimate for children <12 months was 1.0% (95% CI: 0.1 – 7.7) compared to 4.6% (95% CI: 1.2 – 15.4) for children ≥12 months.
Conclusion
Despite varying reporting practices, we found Shigella to be an important contributor to diarrhea in many settings in the Americas with substantial heterogeneity. Limited geographic representation and variable reporting of age group specific estimates were the major gaps in data. Investment in Shigella surveillance in the Americas using a standardized methodology can contribute to accelerating Shigella vaccine development in consideration of regional preferences and optimal age of introduction.
Author summary
Shigella infection is a leading cause of diarrhea worldwide and is annually responsible for over 81,000 deaths among children under five. Its burden and growing antibiotic resistance has led the World Health Organization to identify Shigella as a priority pathogen for vaccine development. There are many open discussions surrounding the development and rollout of a Shigella vaccine, including the pathogen serotypes that a vaccine should target and the age group by which complete immunization should be achieved. While the burden of Shigella cases and deaths has been shown to be highest in Africa and Asia, less is known about the burden of Shigella in the Americas. With this systematic review we aimed to synthesize the burden of Shigella diarrhea among children five years and younger in the Americas region to inform vaccine research, development, and regional policymakers. Our findings include gaps in what is currently known about the distribution of Shigella in the region and suggest approaches to improve data collection and reporting moving forward.
Citation: Lubeck-Schricker M, Rivas-Nieto AC, Rosauer J, Mpinganjira S, Malhotra A, Bastias M, et al. (2025) Burden of Shigella among children with diarrhea in the Americas: A systematic review and meta-analysis. PLoS Negl Trop Dis 19(8): e0013393. https://doi.org/10.1371/journal.pntd.0013393
Editor: Ben Pascoe, University of Oxford, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
Received: February 19, 2025; Accepted: July 22, 2025; Published: August 18, 2025
Copyright: © 2025 Lubeck-Schricker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are in the manuscript and its supporting information files.
Funding: This study was completed by the Strategic Analysis, Research, and Training (START) Center at the University of Washington. START is a collaborative effort with, and is supported by the Gates Foundation (Investment ID INV-033228). The funder proposed the study design but had no role in data collection or analysis.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: CFL declares grant support from HilleVax Inc to his institution.
Introduction
Shigella infection is a leading cause of diarrhea worldwide. In 2021, this Gram-negative bacterium was estimated to be responsible for over 81,000 deaths and over 7.3 million disability adjusted life years (DALYs) in children under five per year [1]. It is also estimated to contribute an additional 13,600 deaths annually due to malnutrition and stunted growth attributed to Shigella’s inflammatory and intestinal destruction mechanism of action [2]. Beyond its population health impacts, Shigella diarrhea is also associated with high household and healthcare system expenditure, which can exacerbate poverty and place significant demands on healthcare systems [3–6].
While the burden of Shigella cases and deaths has been shown to be highest in Africa and Asia, recent multi-site studies have also shown considerable burden in the Americas [7–11]. In 2018, the Global Pediatric Diarrhea Surveillance (GPDS) Network found that while rotavirus was the most common cause of diarrhea hospitalizations globally, Shigella was the leading cause in Central America, with an attributable fraction of 19.2% (95% CI: 11.4 – 28.1), and the third most common cause in South America with an attributable fraction of 11.8% (95% CI: 9.3 – 14.9), compared to 19.2% (95% CI: 12.7 – 28.8) in the Western Pacific and 15.4% (95% CI: 9.1 – 25.1) in South East Asia [12]. In 2012 the Etiology, Risk Factors and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study found a Shigella diarrhea incidence rate of 6.8 cases per 100 child years (95% CI: 3.4 – 11.5) in Brazil and 42.3 cases per 100 child years (95% CI: 32.5 – 53.0) in Peru [13]. Comparatively, between 2000 and 2004 a six country multi-center surveillance study in Asia found an incidence rate of 1.32 cases per 100 child years between 2000 and 2004 in children under five years of age [14]. In the United States, the burden of Shigella diarrhea is lower, with an estimated incidence of 18.15 cases per 100,000 children in the 1–4 year old age group [15]. Across the Americas, the burden of Shigella is particularly concerning given documented multi-drug resistant strains, including in the United States [16,17]. Data from 2014 to 2022 indicated that more than 80% of Shigella sonnei and flexneri isolates in the Americas were resistant to ampicillin, and there has been an increase in resistance to trimethoprim/sulfamethoxazole and increased non-susceptibility to ciprofloxacin from 0.2% to 5.7% within the same period [18,19].
With its increasing antibiotic resistance and continued high-burden, Shigella is a priority pathogen for vaccine development as evidenced by its moving up in priority ranking of the WHO Bacterial Priority Pathogens List, from 25th in 2017 to 8th in 2024 [20,21]. Several Shigella vaccines are in clinical development for the target population of young children with a Phase 3 trial underway and more anticipated in the coming years [22–26]. As policymakers in the Americas eventually consider whether a Shigella vaccine is appropriate for their setting, establishing an evidence-base on the burden estimates of Shigella diarrhea is critical [20]. This systematic review and meta-analysis synthesized the burden of Shigella diarrhea among children under 72 months (six years) in the Americas region. We gathered information on prevalence, incidence, and attributable fraction of Shigella-related diarrhea in this population, which is essential for informing vaccine research and development, regulation, and immunization-related policy making.
Methods
We conducted a systematic review and meta-analyses to summarize the burden of Shigella diarrhea among children under 72 months of age in the Americas, excluding the U.S., Canada, and Greenland. Children in the low- and middle- income countries of the region were the focus due to the likelihood of a vaccine only being considered for pediatric routine vaccination in those contexts [27]. The protocol for this review was registered on Prospero (ID=CRD42024587471) and the PRISMA checklist for systematic reviews can be found in the supporting information (S1 Table) [28].
Search strategy and selection criteria
We searched published and pre-print articles from PubMed, Embase, SciELO, CINAHL, Global Index Medicus, and Web of Science for this review. Articles written in English, Spanish, Portuguese, and French available in these databases from January 1, 2000 through July 23, 2024 were considered. Publications reporting only on data prior to 2000 were excluded to narrow the scope of this review to more recent burden estimates that can inform future policy. The search incorporated terms related to Shigella and diarrheal disease in children under 72 months of age (see S2 Table for complete search terms). We considered all interventional and observational study designs that enabled estimation of prevalence (proportion of diarrhea cases, hospitalizations, or deaths in which Shigella was identified), incidence (number of Shigella-specific diarrhea episodes per unit of person-time), and/or attributable fraction (the proportion of diarrhea episodes attributed to Shigella based on culture positivity, or molecular detection via PCR/qPCR) [29].
We restricted our inclusion to studies that confirmed Shigella infection by laboratory methods (culture, PCR, or qPCR) and that were conducted in countries of the Americas, excluding the U.S., Canada, and Greenland. Studies also had to report disaggregated data specifically for children aged under 72 months with symptomatic diarrheal disease to be included.
After removing duplicate articles, each title and abstract were independently screened for eligibility by two reviewers (MLS, AR, AM, PP) using Covidence systematic review software [30]. A third independent reviewer resolved any discrepancies between the two initial reviewers. Articles that could not be evaluated based on the abstract were automatically moved to full text review. Articles selected for full text review were screened utilizing the same dual review method described for titles and abstracts. At the full text review stage, the reason for exclusion of each ineligible article was recorded within Covidence. Reasons for exclusion were applied hierarchically beginning with incorrect geography, followed by data collection prior to 2000, study population without diarrhea, lack of laboratory confirmation of Shigella, absence of data disaggregated for children under 72 months, and insufficient information to calculate the required metrics.
Data were extracted from included articles utilizing a pre-specified data extraction template embedded in Covidence. Information on study design and methodology (e.g., follow-up duration and inclusion criteria), study location, number of overall children and/or stool samples and those with Shigella detected, key clinical descriptors (i.e., diarrhea definition), antibiotic use, and laboratory detection methods were extracted. Outcomes (prevalence, incidence, attributable fraction) and associated 95% confidence intervals (CIs) were extracted for the overall study population and any relevant subgroups reported by the manuscript authors such as disaggregated age groups, serotype, antibiotic resistance, healthcare setting, and study site urbanicity.
Publication quality was assessed using an adapted Joanna Briggs Institute (JBI) assessment tool (S3 Table) [31]. Quality assessment and data extraction occurred simultaneously using Covidence. All data extraction and quality assessment were conducted by a single reviewer and quality controlled by a second reviewer in Covidence.
Data analysis
Descriptive tables were compiled to summarize the characteristics of all included studies. Forest plots of prevalence, attributable fraction, and incidence estimates were created to display data across studies according to key subgroups of interest, such as detection method and health care setting. Studies were categorized based on what was explicitly stated in the published article. If the authors did not specify a subgroup, for example urbanicity of the study site, the study would not be included in any category for that subgrouping. For studies that estimated prevalence using qPCR detection methods, we accepted their reported values regardless of the lower-limit of detection, quantitative threshold employed to assign detection, or the test manufacturer. In instances when only raw numbers were reported (such as number of Shigella cases and number of children presenting with diarrhea), Shigella prevalence estimates were calculated by the review team. For all prevalence estimates, the review team calculated 95% CIs using R, assuming a binomial distribution to standardize confidence intervals across studies. All incidence estimates were standardized by the review team to the rate of cases per 100 child-years. For all prevalence and attributable fraction outcome metrics, random effects meta-analyses were conducted for each subgroup of interest when relevant data from at least two studies in any subgroup were present using the “Meta” package in R [32]. A meta-analysis was not conducted across incidence estimates due to notable variability in estimation techniques throughout the literature, limiting comparability across estimates.
Results
Literature search results
Our final search yielded 848 articles from all databases described previously. After removing duplicates, 486 articles remained for title and abstract screening. Of these, 338 titles/abstracts were excluded leaving 148 articles that met eligibility criteria for full-text review. During the full-text assessment, 114 studies were excluded resulting in a final 34 articles included in the review (Fig 1). Quality assessments of the 34 included studies can be found in S1 Fig.
Key characteristics of the included studies are presented in Table 1, with a summary of study-level characteristics in Table 2. The data on the burden of Shigella infections originated from 14 countries, with Brazil and Peru contributing nine publications each (26.4%, respectively) (Fig 2). Among the included studies, 22 (64.7%) were cross-sectional studies. Nine studies (26%) used PCR/qPCR as a method of detection with the remaining using culture-based detection. The four studies that used qPCR specified varying cycle threshold (CT) value cutoffs/ lower limits of detection of less than 30 [53], less than 35 [12,13], and less than 38 [42] for Shigella detection, but did not report copies per milliliter. Studies used variable case definitions for diarrhea, with two explicitly excluding cases of bloody diarrhea [53,40]. Among those that included cases of bloody diarrhea, the reported proportion of such cases among all samples ranged considerably from 2.6% up to 30.8%.
Made with public domain data from Natural Earth. Free vector and raster map data at https://www.naturalearthdata.com/. Terms of use available at https://www.naturalearthdata.com/about/terms-of-use/.
Prevalence results
Across all studies that used culture as the method of detection and reported prevalence (n = 23), the pooled prevalence of Shigella among diarrhea cases was 3.1% (95% CI: 1.6 – 5.8, I2: 93.4%). The pooled prevalence among the 7 studies that used PCR/qPCR molecular methods for detection (using a variety of detection cut-offs) was more than five times higher at 16.5% (95% CI: 11.1 –24.0, I2: 94.6%). Among the culture-based studies, Diniz-Santos et al. (2005) [39] estimated the highest prevalence of 27.5% (95% CI: 20.3 – 36.1) among children <48 months in Brazil between 2002 and 2003 [39]. A few culture-based studies estimated a prevalence of zero from sites in Argentina, Haiti, and Uruguay in 2005, 2013, and 2015, respectively [56,62,66]. The highest prevalence estimate among PCR-based studies came from Honduras in 2017–2018 with 37.8% (95% CI: 31.3 – 44.8) among children 6–35 months while the lowest came from Ecuador in 2003–2005 at 1.5% (95% CI: 0.4 – 5.3) among children <60 months (Fig 3) [65].
A subset of culture-based studies reported the prevalence of Shigella specific to serotypes (n = 5). The pooled Shigella flexneri prevalence was 2.4% (95% CI: 1.0 – 5.5, I2: 74.7%) compared to 2.3% (95% CI: 0.6 – 7.9, I2: 92.8%) for Shigella sonnei. In Brazil, the prevalence of Shigella flexneri was lower than that of Shigella sonnei, while the opposite was true for Argentina and Peru [57,61,67] (Fig 4).
After disaggregating studies by healthcare facility type, the highest pooled prevalence estimates among culture-based studies came from four studies enrolling from health centers/posts (4.8%, 95% CI: 1.5 – 14.8, I2: 92.1%), followed by eight hospital-based studies at 3.8% (95% CI: 1.3 – 10.3, I2: 91.5%), five from a mix of facilities (3.1%, 95% CI: 1.4 – 6.6, I2: 68.9%) and four with active case finding in communities (2.6%, 95% CI: 0.3 –14.7, I2: 97.5%) (Fig 5). Among the culture-based hospital studies, a subset (n = 7) explicitly defined their population as either inpatient or outpatient cases and two reported for both inpatients and outpatients. Among the four studies with inpatient populations by culture, the pooled prevalence was 2.6% (95% CI: 0.9 – 6.9, I2: 88.5%), compared to 2.4% (95% CI: 0.9 – 5.8), I2: 65.3% among the five studies with outpatient hospital cases. PCR-based GPDS data for inpatients from six countries and one other study in Peru had an overall high prevalence of 20.8% (95% CI: 15.5 - 27.4, I2: 86.3%) (Fig 6).
Sixteen culture and four PCR-based studies explicitly described the study setting as urban, peri-urban, or rural. While pooled prevalence estimates suggest that the burden of Shigella is generally lower in urban settings compared to rural settings, heterogeneity across studies resulted in large overlapping confidence intervals. Among culture-based studies, the pooled prevalence from urban studies was 4.0% (95% CI: 1.8 – 8.7, I2: 95.0%) while it was 12.0% (95% CI: 6.9 – 19.9, I2: 96.1%) among rural studies (Fig 7).
Studies used an array of age categories, most commonly by year (every 12 months). Other studies reported different intervals such as every two years, with three studies disaggregating ages less than 12 months old. Among culture-based results, the pooled prevalence estimate for children <12 months was 1.0% (95% CI: 0.1 – 7.7, I2: 78.1%) compared to 4.6% (95% CI: 1.2 – 15.4, I2: 90.2%) for children ≥12 months. Among PCR-based studies, the pooled prevalence estimate for children <12 months was 11.9% (95% CI: 5.9 – 22.3, I2: 84.0%) compared to 26.7% (95% CI: 19.5 – 35.4, I2: 78.8%) for children ≥12 months (Fig 8).
Attributable fraction results
Only four studies (two of which from the same surveillance network) reported the burden of Shigella in terms of attributable fraction. Across the two culture-based estimates, the pooled attributable fraction was 2.9% (95% CI: 1.3 – 6.4, I2: 0.0%) [60]. Three PCR studies presented estimates across several countries, for which the pooled attributable fraction was 11.9% (95% CI: 9.7 – 14.6, I2: 48.8%) (Fig 9) [12].
Incidence results
Fewer studies reported incidence of Shigella diarrhea than prevalence and they used a variety of incidence method calculations ranging from direct ascertainment in a cohort study to facility-based studies that estimated incidence. Two studies conducted in Iquitos, Peru showed particularly high incidence of 37.0 per 100 child-years (95% CI: 33.0 – 42.0) from Kosek (2008) [44], which was a culture-based study, and 42.3 per 100 child-years (95% CI: 32.5 – 53.0) from Platts-Mills (2018) [60], a PCR-based study (Fig 10) conducted in the same study area.
Discussion
This review aimed to describe the burden of Shigella among children five years and younger with diarrhea in the Americas to inform surveillance efforts, vaccine research and development investments, and ultimately aid policymakers with vaccine adoption decision-making. The Americas will be an important region to target for eventual Shigella vaccines due to its high burden and history of rapid vaccine adoption. Across the 34 studies reviewed, we found notable high prevalence, attributable fraction, and incidence estimates of Shigella diarrhea highlighting the burden of this Gram-negative bacteria among children living in the Americas.
This systematic review disaggregated all identified study estimates by detection method, given well known discrepancies between culture and PCR/qPCR-based sensitivities. Among culture-based studies, our meta-analysis identified a pooled Shigella diarrhea prevalence of 2.4%, which is slightly lower than estimates from systematic reviews in other regions. Namely, a systematic review of the prevalence of Shigella in Africa, which did not disaggregate by detection method, found a pooled prevalence of 5.9% [11]. Another systematic review in Southeast Asia, again without detection-disaggregated estimates, identified a pooled prevalence of 5% among children <5 years [68]. Within the Americas region, there are clear differences across burden estimates, however no clear patterns by country emerged that could indicate geographic vaccination priorities.
PCR/qPCR methods consistently result in burden estimates several times higher those from culture in the literature [69]. Our meta-analysis of Shigella prevalence from studies that used qPCR or PCR showed estimates more than five times higher than those by culture, with a pooled prevalence of 16.5%. Although a concern with PCR/qPCR methods is the detection of inactive DNA, culture-negative/molecularly identified Shigella cases appear to have similar severity of diarrhea and similar improvements with antibiotic treatment to culture-confirmed Shigella suggesting similar clinical relevance [70,71]. De-tuning quantitative PCR/qPCR methods, such as by choosing a higher-quantity infection threshold for Shigella detection based on cut-offs that distinguish diarrhea case from asymptomatic control status, may successfully distinguish clinically relevant Shigella cases from asymptomatic carriage at the individual case level. At a population level, attributable fraction calculations have been used to account for asymptomatic carriage estimates in controls. Only one molecular detection-based study (of nine) in this review used a de-tuned detection threshold [53], therefore the pooled PCR/qPCR molecular estimates in this review may be overstating the true Shigella-attributed diarrhea burden . Alignment on the threshold for the number of copies of the ipaH gene warranting likely attribution of diarrhea to Shigella across research studies would be an important step to minimize methodological heterogeneity between studies using molecular methods.
A small subset of studies reported prevalence of Shigella serotypes, specifically the two leading serotypes, S. flexneri and S. sonnei. It is hypothesized that serotype distributions shift from S. flexneri to S. sonnei predominance with economic development as well as water and sanitation infrastructure improvements. This shift is hypothesized to be due to the reduced presence of Plesiomonas shigelloides in contaminated water, a Gram-negative bacterium that shares some antigens with S. sonnei conferring immunity against S. sonnei [15,51,52,54,55]. Our meta-analyses of culture-based estimates show that the overall burden of both serotypes across the region are comparable. At the country level, in 2013 this trend held true for Brazil while Argentina and Peru had higher prevalence of S. flexneri in 2007 and 2002, respectively. The overall lack of Shigella serotype data in published literature makes it difficult to discern these trends over time and contribute to discussions about serotype targeting for vaccine development.
We further disaggregated prevalence study estimates into other subgroups of interest, while maintaining separation by detection method, including the type of health facility from which the study population was identified, and whether the study facilities were in urban or rural settings. Our meta-analysis found higher prevalence of Shigella in health center and hospital settings compared to community-based active case finding studies (see S2 Fig for the health facility subgroup forest plots with attributable fraction and incidence estimates). That Shigella diarrhea is more severe than other causes and that care-seeking tends to identify more severe diarrhea is consistent with other studies [1]. We found a lower pooled prevalence of Shigella among studies conducted in urban settings compared to rural settings, which aligns with findings from other studies that have similarly suggested higher prevalence of Shigella in rural settings, such as in a surveillance-based study of Shigella over 20 years in Bangladesh [72,73]. Uncertainty in pooled estimates with few rural prevalence estimates or differences in infrastructure between settings may explain the heterogeneity.
Age of optimal Shigella vaccine introduction remains an open discussion with general agreement that full protection would ideally occur prior to 12 months of age [74–76]. However, an increasingly crowded infant vaccine schedule may prove challenging. To explore variations in burden, we disaggregated pooled burden estimates by age and found that the prevalence of Shigella was higher among children above 12 months of age compared to younger children, consistent with other studies [77]. However, the majority of the data is cross-sectional and therefore does not explain how much Shigella diarrhea could be averted by a vaccine introduced at different ages. The MAL-ED study [60] ascertained age of first infection across seven countries, including Peru, and found the median time of first infection with Shigella to be 14 months of age [77]. Only two culture-based studies disaggregated the prevalence of Shigella among children <6 months compared to those 6–12 months old. While Manrique-Abril et al. [47] found comparable prevalence across these two groups, Perales et al. [57] demonstrated a burden more than twice as high among 6–12 month-olds compared to children <6 months old, a finding consistent with age-stratified Shigella prevalence in MAL-ED [47,57,77]. These data suggest that studies reporting Shigella burden in 0–12-month-old children may mask a notable burden among the 6–12-month sub-group. The one included study that presented age-stratified Shigella diarrhea incidence rates (Kosek 2008)[44] reported a peak Shigella diarrhea incidence of 50 cases/100 child-years in 12–23 month-olds but also noted a non-negligible burden in 6–11 months-olds (22 cases/100 child-years) [44]. Given uncertainty about precise timing of Shigella vaccine introduction, future studies should disaggregate their reporting of Shigella burden data in 3–6-month age categories, particularly among children under two years of age.
Incidence rates were less commonly reported in studies, likely due to the additional complexity of enumerating a population at risk and ensuring all possible cases are accounted for [29]. In the two studies that utilized a standard prospective cohort study design with active diarrhea episode ascertainment, including that which did not lead to care-seeking, incidence rates of Shigella diarrhea were exceptionally high compared to other incidence estimates, irrespective of detection method [44,59]. Incidence rates provide a better understanding of disease burden as they are unbiased by health care seeking and social exclusion, which affect ascertainment in health care centers, particularly in highly marginalized populations [78].
Incidence studies that focused on health-facility ascertainment of cases, both outpatient and inpatient, and exclusively inpatients, had lower incidence rates, consistent with rarer, but costly, more severe disease [12,43]. Health care system costs, and costs averted by introduction of a Shigella vaccine by preventing outpatient and inpatient visits, will be key factors for country decision makers to consider when faced with a potentially effective and available Shigella vaccine (see S2 Fig for forest plot of attributable fraction estimates among only inpatient populations). The cost of an eventual Shigella vaccine will also be an important factor for policy-makers. Larger vaccine markets help to drive down prices through initiatives like pooled procurement, making vaccines more accessible for the lowest income settings. This review highlights that Shigella diarrhea appears to be distributed across the Americas and expanding surveillance in the region may further demonstrate a universal and notable Shigella burden throughout the region.
Beyond cost-effectiveness, vaccine developers must also consider that country immunization programs are becoming saturated, which is reflected in the number of vaccination visits and shots per visit, where the same number of health workers are asked to manage increasingly complex vaccination schedules [74]. As such, combination vaccine strategies based on identified and validated regional priority vaccine targets have been raised as the way forward for Shigella vaccines [74,79]. This review may further inform regional decision makers on the relative burden of Shigella and therefore its relevance to the research and development of a combination vaccine.
The majority of studies included in this review were conducted from populations within Brazil and Peru, with minimal representation in the rest of the Americas region resulting in limited generalizability of results. In addition to data from more countries, sub-national data is needed to inform a better understanding of Shigella epidemiology in the Americas. The high burden in Iquitos, Peru, confirmed by multi-country studies including sites in Asia and Africa, has led some to believe the Amazon region is a particularly high-risk place for Shigella compared to the rest of the Americas due to infrastructure- and climate-related factors that may promote bacteria growth [44,59]. Few studies estimated the burden of Shigella in other communities within the Amazon region, limiting the ability to generalize the burden observed in Iquitos to other areas of the Amazon in Peru, as well as Brazil, Colombia, and Ecuador (see S4 Table for all burden estimates from study sites in the Amazon region). It is also noteworthy that incidence rates from sites selected for research studies may not reflect the true population-based incidence in the region because areas with known high disease burden are more likely to be selected for study and intervention. Conversely, children in the lowest resourced and most isolated settings who generally have the lowest access to state-of-the-art diagnostics may not be represented in the research studies reported in this review.
Beyond limited variation in the geographic scope of studies in the region, another limitation of our systematic review is the overall heterogeneity of reporting practices across articles, resulting in the exclusion of valid and useful data across various subgroup analyses, for example, prevalence by age. In some cases, the lack of data available for comparison across studies resulted in reduced power of the meta-analyses to estimate pooled metrics and thus produced imprecise corresponding confidence intervals. Some studies excluded children with previous antibiotic use and/or children with co-infections which further limited comparability across studies. Regarding seasonality of Shigella, this review did not restrict study inclusion by duration of recruitment, which could result in comparison of specific seasonal burden estimates to those from year-round data collection. Finally, most of the studies included in this review (n = 27) were facility-based thus limiting understanding of the burden of Shigella to the region’s health systems, rather than that of the general population. Despite the overall limited number of studies that met inclusion criteria and the varying data collection and reporting practices of those included studies, we were able to produce several informative meta-analyses to identify pooled burden estimates across key subgroups relevant to vaccine development and eventual deployment considerations.
Overall, our findings on the burden of Shigella in the Americas emphasize the need to further study Shigella incidence and prevalence. Importantly, data would be most useful with a standardized detection methodology, such as a uniform qPCR platform with a de-tuned threshold, across a variety of geographic settings, including throughout the Amazon region, and to report data disaggregated by subpopulations of interest to contribute to key vaccine discussions. These findings may incentivize investment in Shigella surveillance and contribute to accelerating Shigella vaccine development, and eventual uptake, in consideration of regional preferences, including multi-pathogen vaccine development strategies.
Supporting information
S1 Fig. Quality assessment of 34 included studies.
https://doi.org/10.1371/journal.pntd.0013393.s001
(DOCX)
S2 Fig. Additional forest plots of Shigella burden.
https://doi.org/10.1371/journal.pntd.0013393.s002
(DOCX)
S1 Table. PRISMA 2020 checklist for systematic reviews.
https://doi.org/10.1371/journal.pntd.0013393.s003
(DOCX)
S3 Table. Adapted Joanna Briggs Institute (JBI) quality assessment tool.
https://doi.org/10.1371/journal.pntd.0013393.s005
(DOCX)
S4 Table. Burden estimates from study sites in the Amazon region.
https://doi.org/10.1371/journal.pntd.0013393.s006
(DOCX)
Acknowledgments
The authors would like to acknowledge Teresa Jewell at the University of Washington Health Sciences Library for her help developing a literature search strategy. We would further like to thank Ana Krause for her copyedit of the manuscript and the leadership and operations team at the UW START Center for their administrative support.
References
- 1.
GBD Results. In: Institute for Health Metrics and Evaluation [Internet]. [cited 19 Oct 2024]. Available from: https://vizhub.healthdata.org/gbd-results
- 2. Anderson JD 4th, Bagamian KH, Muhib F, Amaya MP, Laytner LA, Wierzba T, et al. Burden of enterotoxigenic Escherichia coli and shigella non-fatal diarrhoeal infections in 79 low-income and lower middle-income countries: a modelling analysis. Lancet Glob Health. 2019;7(3):e321–30. pmid:30784633
- 3. Baral R, Nonvignon J, Debellut F, Agyemang SA, Clark A, Pecenka C. Cost of illness for childhood diarrhea in low- and middle-income countries: a systematic review of evidence and modelled estimates. BMC Public Health. 2020;20(1):619. pmid:32370763
- 4. Das R, Haque MA, Chisti MJ, Faruque ASG, Ahmed T. Associated factors, post infection child growth, and household cost of invasive enteritis among under 5 children in Bangladesh. Sci Rep. 2021;11(1):12738. pmid:34140589
- 5. Memirie ST, Metaferia ZS, Norheim OF, Levin CE, Verguet S, Johansson KA. Household expenditures on pneumonia and diarrhoea treatment in Ethiopia: a facility-based study. BMJ Glob Health. 2017;2(1):e000166. pmid:28589003
- 6. Riewpaiboon A, Youngkong S, Sreshthaputra N, Stewart JF, Samosornsuk S, Chaicumpa W, et al. A cost function analysis of shigellosis in Thailand. Value Health. 2008;11(Suppl 1):S75–83. pmid:18387071
- 7. Ayele B, Beyene G, Alemayehu M, Dekebo A, Mekonnen Z, Nigussie G. Prevalence and Antimicrobial-Resistant Features of Shigella Species in East Africa from 2015-2022: A Systematic Review and Meta-Analysis. Interdiscip Perspect Infect Dis. 2023;2023:8277976. pmid:37692062
- 8. Baker S, The HC. Recent insights into Shigella: a major contributor to the global diarrhoeal disease burden. Curr Opin Infect Dis. 2018;31(5):449–54. pmid:30048255
- 9. Barrantes K, Achí R. The importance of integrons for development and propagation of resistance in Shigella: the case of Latin America. Braz J Microbiol. 2016;47(4):800–6. pmid:27528086
- 10. Khalil IA, Troeger C, Blacker BF, Rao PC, Brown A, Atherly DE, et al. Morbidity and mortality due to shigella and enterotoxigenic Escherichia coli diarrhoea: the Global Burden of Disease Study 1990-2016. Lancet Infect Dis. 2018;18(11):1229–40. pmid:30266330
- 11. Nyarkoh R, Odoom A, Donkor ES. Prevalence of Shigella species and antimicrobial resistance patterns in Africa: systematic review and meta-analysis. BMC Infect Dis. 2024;24(1):1217. pmid:39472797
- 12. Cohen AL, Platts-Mills JA, Nakamura T, Operario DJ, Antoni S, Mwenda JM, et al. Aetiology and incidence of diarrhoea requiring hospitalisation in children under 5 years of age in 28 low-income and middle-income countries: findings from the Global Pediatric Diarrhea Surveillance network. BMJ Glob Health. 2022;7(9):e009548. pmid:36660904
- 13. Platts-Mills JA, Liu J, Rogawski ET, Kabir F, Lertsethtakarn P, Siguas M, et al. Use of quantitative molecular diagnostic methods to assess the aetiology, burden, and clinical characteristics of diarrhoea in children in low-resource settings: a reanalysis of the MAL-ED cohort study. Lancet Glob Health. 2018;6(12):e1309–18.
- 14. von Seidlein L, Kim DR, Ali M, Lee H, Wang X, Thiem VD, et al. A multicentre study of Shigella diarrhoea in six Asian countries: disease burden, clinical manifestations, and microbiology. Sansonetti PJ, editor. PLoS Med. 2006;3(9):e353. pmid:16968124
- 15.
Centers for Disease Control and Prevention (CDC). National enteric disease surveillance: Shigella annual report, 2016. Atlanta, Georgia: US Department of Health and Human Services; 2018.
- 16. Baker KS, Campos J, Pichel M, Della Gaspera A, Duarte-Martínez F, Campos-Chacón E, et al. Whole genome sequencing of Shigella sonnei through PulseNet Latin America and Caribbean: advancing global surveillance of foodborne illnesses. Clin Microbiol Infect. 2017;23(11):845–53. pmid:28389276
- 17.
CDC. National antimicrobial resistance monitoring system for enteric bacteria (NARMS): Human isolates surveillance report for 2014 (Final report). Atlanta, Georgia: US Department of Health and Human Services; 2016.
- 18.
Gutiérrez LA. PAHO/WHO Data - 2. Resistance percentages for selected pathogens | PAHO/WHO. In: Pan American Health Organization/ World Health Organization [Internet]. 11 Mar 2015 [cited 12 Jan 2025]. Available from: https://www3.paho.org/data/index.php/en/mnu-topics/antimicrobial-resistance/571-amr-vig-en.html
- 19. Quino W, Bellido G, Flores-León D, Caro-Castro J, Mestanza O, Lucero J, et al. Trends in antimicrobial resistance of Shigella species in Peru, 2011-2020. JAC Antimicrob Resist. 2023;5(5):dlad110. pmid:37901588
- 20. Hasso-Agopsowicz M, Hwang A, Hollm-Delgado M-G, Umbelino-Walker I, Karron RA, Rao R, et al. Identifying WHO global priority endemic pathogens for vaccine research and development (R&D) using multi-criteria decision analysis (MCDA): an objective of the Immunization Agenda 2030. EBioMedicine. 2024;110:105424. pmid:39500705
- 21.
World Health Organization. WHO bacterial priority pathogens list 2024: bacterial pathogens of public health importance, to guide research, development, and strategies to prevent and control antimicrobial resistance. 1st ed. Geneva: World Health Organization; 2024.
- 22. MacLennan CA, Grow S, Ma L-F, Steele AD. The Shigella Vaccines Pipeline. Vaccines (Basel). 2022;10(9):1376. pmid:36146457
- 23. Raso MM, Arato V, Gasperini G, Micoli F. Toward a Shigella Vaccine: Opportunities and Challenges to Fight an Antimicrobial-Resistant Pathogen. Int J Mol Sci. 2023;24(5):4649. pmid:36902092
- 24.
Vaccine profiles: Shigella. [cited 9 Oct 2024]. Available from: https://www.gavi.org/vaccineswork/vaccine-profiles-shigella
- 25. Vannice K, MacLennan CA, Long J, Steele AD. Optimizing Vaccine Trials for Enteric Diseases: The Enterics for Global Health (EFGH) Shigella Surveillance Study. Open Forum Infect Dis. 2024;11(Suppl 1):S1–5. pmid:38532964
- 26.
Beijing Zhifei Lvzhu Biopharmaceutical Co., Ltd. A Multicenter, Randomized, Double-blind, Placebo-Controlled Phase III Clinical Trial to Evaluate the Efficacy, Immunogenicity and Safety of S. Flexneriza-S. Sonnei Bivalent Conjugate Vaccine in Volunteers Aged From 6 Months to 5 Years. clinicaltrials.gov; 2022 Jan. Report No.: NCT05156528. Available from: https://clinicaltrials.gov/study/NCT05156528
- 27.
World Health Organization. WHO Preferred Product Characteristics for Vaccines Against Shigella. 1st ed. Geneva: World Health Organization; 2021.
- 28.
[cited 2 Feb 2025]. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=587471
- 29. Di Maso M, Bravi F, Polesel J, Negri E, Decarli A, Serraino D, et al. Attributable fraction for multiple risk factors: Methods, interpretations, and examples. Stat Methods Med Res. 2020;29(3):854–65. pmid:31074326
- 30.
Veritas Health Innovation. Covidence - Better systematic review management. In: Covidence [Internet]. 2024 [cited 12 Dec 2024]. Available from: https://www.covidence.org/
- 31.
JBI Critical Appraisal Tools | JBI. [cited 12 Dec 2024]. Available from: https://jbi.global/critical-appraisal-tools
- 32. Schwarzer G, Chemaitelly H, Abu-Raddad LJ, Rücker G. Seriously misleading results using inverse of Freeman-Tukey double arcsine transformation in meta-analysis of single proportions. Res Synth Methods. 2019;10(3):476–83. pmid:30945438
- 33. Arvelo W, Hall AJ, Henao O, Lopez B, Bernart C, Moir JC, et al. Incidence and etiology of infectious diarrhea from a facility-based surveillance system in Guatemala, 2008-2012. BMC Public Health. 2019;19(1):1340. pmid:31640646
- 34.
Balbachán DSE, Merino DLA, Merino DDE, Balbachán DML, Miranda A. Resistencia antimicrobiana de bacterias causantes de diarreas en niños de Corrientes, Argentina.
- 35. Becker-Dreps S, Bucardo F, Vilchez S, Zambrana LE, Liu L, Weber DJ, et al. Etiology of childhood diarrhea after rotavirus vaccine introduction: a prospective, population-based study in Nicaragua. Pediatr Infect Dis J. 2014;33(11):1156–63. pmid:24879131
- 36. Casabonne C, González A, Aquili V, Balagué C. Prevalence and Virulence Genes of Shigella spp. Isolated from Patients with Diarrhea in Rosario, Argentina. Jpn J Infect Dis. 2016;69(6):477–81. pmid:26902216
- 37. Cermeño JR, Hernández de Cuesta I, Camaripano M, Medina N, Guevara A, Hernández Rivero C. Etiología de diarrea aguda en niños menores de 5 años Ciudad Bolívar, Venezuela. Revista de la Sociedad Venezolana de Microbiología. 2008;28:55–60.
- 38. Cornejo-Tapia A, Orellana-Peralta F, Weilg P, Bazan-Mayra J, Cornejo-Pacherres H, Ulloa-Urizar G, et al. Etiology, epidemiology and clinical characteristics of acute diarrhea in hospitalized children in rural Peru. J Infect Dev Ctries. 2017;11(11):826–32. pmid:31618180
- 39. Diniz-Santos DR, Santana JS, Barretto JR, Andrade MGM, Silva LR. Epidemiological and microbiological aspects of acute bacterial diarrhea in children from Salvador, Bahia, Brazil. Braz J Infect Dis. 2005;9(1):77–83. pmid:15947851
- 40. Gaensbauer JT, Lamb M, Calvimontes DM, Asturias EJ, Kamidani S, Contreras-Roldan IL, et al. Identification of Enteropathogens by Multiplex PCR among Rural and Urban Guatemalan Children with Acute Diarrhea. Am J Trop Med Hyg. 2019;101(3):534–40. pmid:31392942
- 41.
Gambandé T, Damiano M, Borda’ N, Notario R, Aita J. Prevalencia de las bacterias causantes de diarrea en pacientes de un hospital de Rosario, Argentina.
- 42. Garcia Bardales PF, Schiaffino F, Huynh S, Paredes Olortegui M, Peñataro Yori P, Pinedo Vasquez T, et al. “Candidatus Campylobacter infans” detection is not associated with diarrhea in children under the age of 2 in Peru. PLoS Negl Trop Dis. 2022;16(10):e0010869. pmid:36251729
- 43. Hegde S, Benoit SR, Arvelo W, Lindblade K, López B, McCracken JP, et al. Burden of laboratory-confirmed shigellosis infections in Guatemala 2007-2012: results from a population-based surveillance system. BMC Public Health. 2019;19(Suppl 3):474. pmid:32326929
- 44. Kosek M, Yori PP, Pan WK, Olortegui MP, Gilman RH, Perez J, et al. Epidemiology of highly endemic multiply antibiotic-resistant shigellosis in children in the Peruvian Amazon. Pediatrics. 2008;122(3):e541-9. pmid:18710884
- 45. Larrosa-Haro A, Macias-Rosales R, Sánchez-Ramírez CA, Cortés-López MC, Aguilar-Benavides S. Seasonal variation of enteropathogens in infants and preschoolers with acute diarrhea in western Mexico. J Pediatr Gastroenterol Nutr. 2010;51(4):534–6. pmid:20706147
- 46. Lima AAM, Oliveira DB, Quetz JS, Havt A, Prata MMG, Lima IFN, et al. Etiology and severity of diarrheal diseases in infants at the semiarid region of Brazil: A case-control study. PLoS Negl Trop Dis. 2019;13(2):e0007154. pmid:30735493
- 47. Manrique-Abril FG, Tigne y Diane B, Bello SE, Ospina JM. Diarrhoea-causing agents in children aged less than five in Tunja, Colombia. Rev Salud Publica (Bogota). 2006;8(1):88–97. pmid:16703965
- 48. Moreno ACR, Filho AF, Gomes T do AT, Ramos STS, Montemor LPG, Tavares VC, et al. Etiology of childhood diarrhea in the northeast of Brazil: significant emergent diarrheal pathogens. Diagn Microbiol Infect Dis. 2010;66(1):50–7. pmid:18508227
- 49. Moura MDRSDALD, Mello MJGD, Calábria WB, Germano EM, Maggi RRS, Correia JDB. Frequência de Escherichia coli e sua sensibilidade aos antimicrobianos em menores de cinco anos hospitalizados por diarreia aguda. Rev Bras Saude Mater Infant. 2012;12:173–82.
- 50. Nazate Chuga ZR, Ramos Sánchez RE, Mejía Álvarez ET, Villarreal Ger MC. Principales agentes etiológicos de las enfermedades diarreicas agudas infantiles en Chimborazo, Ecuador. BMSA. 2022;62(4):714–20.
- 51. Ochoa TJ, Chea-Woo E, Baiocchi N, Pecho I, Campos M, Prada A, et al. Randomized double-blind controlled trial of bovine lactoferrin for prevention of diarrhea in children. J Pediatr. 2013;162(2):349–56. pmid:22939927
- 52. Ochoa TJ, Ecker L, Barletta F, Mispireta ML, Gil AI, Contreras C, et al. Age-related susceptibility to infection with diarrheagenic Escherichia coli among infants from Periurban areas in Lima, Peru. Clin Infect Dis. 2009;49(11):1694–702. pmid:19857163
- 53. Operario DJ, Platts-Mills JA, Nadan S, Page N, Seheri M, Mphahlele J, et al. Etiology of Severe Acute Watery Diarrhea in Children in the Global Rotavirus Surveillance Network Using Quantitative Polymerase Chain Reaction. J Infect Dis. 2017;216(2):220–7. pmid:28838152
- 54. Orlandi PP, Magalhães GF, Matos NB, Silva T, Penatti M, Nogueira PA, et al. Etiology of diarrheal infections in children of Porto Velho (Rondonia, Western Amazon region, Brazil). Braz J Med Biol Res. 2006;39(4):507–17. pmid:16612474
- 55. Patzi-Vargas S, Zaidi MB, Perez-Martinez I, León-Cen M, Michel-Ayala A, Chaussabel D, et al. Diarrheagenic Escherichia coli carrying supplementary virulence genes are an important cause of moderate to severe diarrhoeal disease in Mexico. PLoS Negl Trop Dis. 2015;9(3):e0003510. pmid:25738580
- 56. Peirano V, Bianco MN, Navarro A, Schelotto F, Varela G. Diarrheagenic Escherichia coli Associated with Acute Gastroenteritis in Children from Soriano, Uruguay. Can J Infect Dis Med Microbiol. 2018;2018:8387218. pmid:30515254
- 57. Perales MD, Maximo C, Carmen Q. Infección por Campylobacter y Shigella como causa de diarrea aguda acuosa en niños menores de dos años en el distrito de La Victoria, Lima – Perú*. Rev Peru Med Exp Salud Publica. 2002;19.
- 58. Pérez-Schael I, Salinas B, González R, Salas H, Ludert JE, Escalona M, et al. Rotavirus mortality confirmed by etiologic identification in Venezuelan children with diarrhea. Pediatr Infect Dis J. 2007;26(5):393–7. pmid:17468648
- 59. Platts-Mills JA, Liu J, Rogawski ET, Kabir F, Lertsethtakarn P, Siguas M, et al. Use of quantitative molecular diagnostic methods to assess the aetiology, burden, and clinical characteristics of diarrhoea in children in low-resource settings: a reanalysis of the MAL-ED cohort study. Lancet Glob Health. 2018;6(12):e1309–18. pmid:30287127
- 60. Platts-Mills JA, Babji S, Bodhidatta L, Gratz J, Haque R, Havt A, et al. Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED). Lancet Glob Health. 2015;3(9):e564-75. pmid:26202075
- 61. Sousa MÂB, Mendes EN, Collares GB, Péret-Filho LA, Penna FJ, Magalhães PP. Shigella in Brazilian children with acute diarrhoea: prevalence, antimicrobial resistance and virulence genes. Mem Inst Oswaldo Cruz. 2013;108(1):30–5. pmid:23440111
- 62. Steenland MW, Joseph GA, Lucien MAB, Freeman N, Hast M, Nygren BL, et al. Laboratory-confirmed cholera and rotavirus among patients with acute diarrhea in four hospitals in Haiti, 2012-2013. Am J Trop Med Hyg. 2013;89(4):641–6. pmid:24106190
- 63. Urbina D, Arzuza O, Young G, Parra E, Castro R, Puello M. Rotavirus type A and other enteric pathogens in stool samples from children with acute diarrhea on the Colombian northern coast. Int Microbiol. 2003;6(1):27–32. pmid:12687410
- 64.
Yepes MAU, Villamizar LAR, González YAG, Gamboa LEO, Santamaría SMR. Aislamientos de patógenos comunes asociados con enfermedad diarreica aguda en menores de cinco años, Bucaramanga, Colombia. 2009;12.
- 65. Vieira N, Bates SJ, Solberg OD, Ponce K, Howsmon R, Cevallos W, et al. High prevalence of enteroinvasive Escherichia coli isolated in a remote region of northern coastal Ecuador. Am J Trop Med Hyg. 2007;76(3):528–33.
- 66. Gambandé T, Damiano M, Borda’ N, Notario R, Aita J. Prevalencia de las bacterias causantes de diarrea en pacientes de un hospital de Rosario, Argentina. Revista de Salud Pública. 2023;68(1):1–10.
- 67.
Balbachán DSE, Merino DLA, Merino DDE, Balbachán DML, Miranda A. Resistencia antimicrobiana de bacterias causantes de diarreas en niños de Corrientes, Argentina.
- 68. Muzembo BA, Kitahara K, Mitra D, Ohno A, Khatiwada J, Dutta S, et al. Shigellosis in Southeast Asia: A systematic review and meta-analysis. Travel Med Infect Dis. 2023;52:102554. pmid:36792021
- 69. Liu J, Platts-Mills JA, Juma J, Kabir F, Nkeze J, Okoi C, et al. Use of quantitative molecular diagnostic methods to identify causes of diarrhoea in children: a reanalysis of the GEMS case-control study. Lancet. 2016;388(10051):1291–301. pmid:27673470
- 70. Pavlinac PB, Platts-Mills JA, Tickell KD, Liu J, Juma J, Kabir F, et al. The Clinical Presentation of Culture-positive and Culture-negative, Quantitative Polymerase Chain Reaction (qPCR)-Attributable Shigellosis in the Global Enteric Multicenter Study and Derivation of a Shigella Severity Score: Implications for Pediatric Shigella Vaccine Trials. Clin Infect Dis. 2021;73(3):e569–79. pmid:33044509
- 71. Pavlinac PB, Platts-Mills JA, Liu J, Atlas HE, Gratz J, Operario D, et al. Azithromycin for Bacterial Watery Diarrhea: A Reanalysis of the AntiBiotics for Children With Severe Diarrhea (ABCD) Trial Incorporating Molecular Diagnostics. J Infect Dis. 2024;229(4):988–98. pmid:37405406
- 72. Nuzhat S, Das R, Das S, Islam SB, Palit P, Haque MA, et al. Antimicrobial resistance in shigellosis: A surveillance study among urban and rural children over 20 years in Bangladesh. PLoS One. 2022;17(11):e0277574. pmid:36409683
- 73. Ferdous F, Ahmed S, Farzana FD, Das J, Malek MA, Das SK, et al. Aetiologies of diarrhoea in adults from urban and rural treatment facilities in Bangladesh. Epidemiol Infect. 2015;143(7):1377–87. pmid:25222698
- 74. Hausdorff WP, Madhi SA, Kang G, Kaboré L, Tufet Bayona M, Giersing BK. Facilitating the development of urgently required combination vaccines. Lancet Glob Health. 2024;12(6):e1059–67. pmid:38636529
- 75. Passwell JH, Ashkenazi S, Banet-Levi Y, Ramon-Saraf R, Farzam N, Lerner-Geva L, et al. Age-related efficacy of Shigella O-specific polysaccharide conjugates in 1-4-year-old Israeli children. Vaccine. 2010;28(10):2231–5. pmid:20056180
- 76.
WHO preferred product characteristics for vaccines against Shigella. [cited 12 Dec 2024]. Available from: https://www.who.int/publications/i/item/9789240036741
- 77. Rogawski McQuade ET, Shaheen F, Kabir F, Rizvi A, Platts-Mills JA, Aziz F, et al. Epidemiology of Shigella infections and diarrhea in the first two years of life using culture-independent diagnostics in 8 low-resource settings. PLoS Negl Trop Dis. 2020;14(8):e0008536. pmid:32804926
- 78. Ward MM. Estimating disease prevalence and incidence using administrative data: some assembly required. J Rheumatol. 2013;40(8):1241–3. pmid:23908527
- 79. Baqar S, Bonavia A, Louis Bourgeois A, Campo JJ, Clifford A, Hanevik K, et al. The 2022 Vaccines Against Shigella and Enterotoxigenic Escherichia coli (VASE) Conference: Summary of breakout workshops. Vaccine. 2024;42(7):1445–53. pmid:38036392