Beyond Acute Jaundice: refining case definitions for suspected hepatitis E in South Sudan and Bangladesh

Beyond Acute Jaundice: refining case definitions for suspected hepatitis E in South Sudan and Bangladesh | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Beyond Acute Jaundice: refining case definitions for suspected hepatitis E in South Sudan and Bangladesh Aybüke Koyuncu , Repon C. Paul , Robin Nesbitt , Kinya Vincent Asilaza , Catia Alvarez , Kajal C. Banik , Joseph Wamala , Arifa Nazneen , Melat Haile , Shariful Amin Sumon , Etienne Gignoux , Kishor K. Paul , Manuel Albela , Arifa Akram , Frederick Beden Loro , M. Salim Uzzaman , Duol Biem , Monica Rull , Stephen P. Luby , Isabella Eckerle , John Rumunu , Iza Ciglenecki , Emily S. Gurley , Andrew S Azman doi: https://doi.org/10.1101/2025.10.03.25337273 Aybüke Koyuncu 1 Johns Hopkins University , USA 2 Epicentre , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Repon C. Paul 3 icddr ,b, Dhaka, Bangladesh 4 Centre for Big Data Research in Health, University of New South Wales , Sydney, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Robin Nesbitt 2 Epicentre , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kinya Vincent Asilaza 6 Médecins Sans Frontières , South Sudan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Catia Alvarez 10 Geneva Centre for Emerging Viral Diseases, University Hospitals of Geneva and Department of Medicine, Faculty of Medicine , Geneva, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kajal C. Banik 3 icddr ,b, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joseph Wamala 9 World Health Organisation , South Sudan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Arifa Nazneen 3 icddr ,b, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Melat Haile 8 Médecins Sans Frontières , Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shariful Amin Sumon 3 icddr ,b, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Etienne Gignoux 2 Epicentre , France 8 Médecins Sans Frontières , Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kishor K. Paul 3 icddr ,b, Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Manuel Albela 8 Médecins Sans Frontières , Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Arifa Akram 4 Centre for Big Data Research in Health, University of New South Wales , Sydney, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Frederick Beden Loro 9 World Health Organisation , South Sudan Find this author on Google Scholar Find this author on PubMed Search for this author on this site M. Salim Uzzaman 5 Institute of Epidemiology, Disease Control and Research , Government of the People’s Republic of Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Duol Biem 7 Ministry of Health , South Sudan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Monica Rull 8 Médecins Sans Frontières , Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stephen P. Luby 12 Infectious Diseases and Geographic Medicine, Stanford University , USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Isabella Eckerle 10 Geneva Centre for Emerging Viral Diseases, University Hospitals of Geneva and Department of Medicine, Faculty of Medicine , Geneva, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Rumunu 7 Ministry of Health , South Sudan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Iza Ciglenecki 8 Médecins Sans Frontières , Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emily S. Gurley 1 Johns Hopkins University , USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew S Azman 1 Johns Hopkins University , USA 8 Médecins Sans Frontières , Switzerland 10 Geneva Centre for Emerging Viral Diseases, University Hospitals of Geneva and Department of Medicine, Faculty of Medicine , Geneva, Switzerland 11 Division of Tropical and Humanitarian Medicine, Geneva University Hospitals , Geneva, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: azman{at}jhu.edu Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Summary The true burden of hepatitis E is poorly understood due to a lack of routine diagnostic testing and nonspecific symptoms. We evaluated the sensitivity and specificity of international case definitions for suspected hepatitis E and explored whether alternative case definitions could more accurately identify those with true hepatitis E, thus improving our ability to interpret surveillance data. We used data from acute jaundice surveillance in South Sudan (March-December 2022) and Bangladesh (December 2014-September 2017). Individuals seeking care with acute jaundice syndrome (AJS) were asked about signs/symptoms of hepatitis E and underwent testing with anti-hepatitis E virus (HEV) IgM ELISA. We used an ensemble of classification models to assess how well signs/symptoms could distinguish between AJS with and without HEV. To explore alternative case definitions, we estimated the sensitivity and specificity of all combinations of signs/symptoms. Among patients with AJS, 20% in South Sudan and 38% in Bangladesh had IgM antibodies. International case definitions for suspected hepatitis E had variable sensitivity (53-96%) and specificity (6-60%) across study populations. Alternative case definitions had poor discrimination in both populations (AUC SouthSudan =0.64; 95% Confidence Interval (CI): 0.57, 0.71; AUC Bangladesh = 0.60; 95% CI: 0.57, 0.63). No alternative case definitions had both sensitivity and specificity above 60% in both study populations. Acute jaundice surveillance in two distinct populations revealed that signs/symptoms alone are insufficient to distinguish HEV-related cases from other causes of acute jaundice. Accurately characterizing the burden of hepatitis E and assessing the cost effectiveness of vaccines will require expanded use of diagnostic testing. Introduction Hepatitis E genotypes 1 and 2 disproportionately affect populations in low-income settings with limited resources for surveillance and outbreak response ( 1 ). Hepatitis E virus (HEV) is an epidemic-prone pathogen transmitted through the fecal-oral route, and universal access to clean water, sanitation, and hygiene (WASH) is needed for long-term control and elimination ( 1 ). HEV239 vaccine (Hecolin; Innovax, Xiamen, China) is safe and highly efficacious in preventing hepatitis E disease ( 2 , 3 ) and is a potential tool to for protecting vulnerable populations such as pregnant women, for whom case fatality risks can be up to 25% and the risk of having a miscarriage and stillbirth is heightened ( 4 – 7 ). The World Health Organization (WHO) has not recommended the routine use of the vaccine in HEV-endemic countries, citing insufficient data on the incidence of hepatitis E in the general population as a key barrier ( 8 ). Understanding the burden of hepatitis E is complicated by a lack of routine testing for hepatitis E among acute jaundice cases, and non-specific symptoms (e.g., acute jaundice, fever) that are shared with other diseases ( 9 ). Though diagnostics for hepatitis E can have high sensitivity and specificity ( 10 – 13 ), many settings where hepatitis E occurs lack the laboratory infrastructure needed for confirmatory testing of suspected hepatitis E cases and also limited availability of rapid diagnostic tests that can be used at point-of-care. The cost of RDTs (4-11.5 USD per test ( 14 )) is likely to remain a barrier to broad use in the near future, especially since hepatitis E treatment is typically supportive care ( 5 ) and diagnostic confirmation is unlikely to change patient management. In the absence of diagnostic capacity, surveillance for hepatitis E in low-income settings is typically based on diagnosis of acute jaundice syndrome (AJS) ( 15 ), and outbreaks are typically identified when the number of AJS cases that seek care at a facility is higher than expected during a defined period or if clusters of fulminant hepatitis and deaths are identified in pregnant women. Reports of hepatitis E outbreaks in the published and grey literature frequently cite uncertain and/or incorrect initial conclusions about outbreak aetiology, and outbreaks are often initially suspected to be due to malaria ( 16 ) or yellow fever ( 17 , 18 ). A better understanding of the likelihood that acutely jaundiced individuals truly have hepatitis E can help decision-makers understand when pathogen-specific outbreak response activities are needed. The WHO hepatitis E outbreak toolbox includes several international case definitions for suspected hepatitis E proposed by WHO and other non-governmental organizations (NGOs) ( 19 ). The suspected case definitions include different combinations of signs and symptoms that correspond to acute illness (e.g., fever) and signs of liver damage (e.g., jaundice, nausea). At the time of writing this, we are unable to identify any studies in the published literature evaluating the sensitivity and specificity of different international case definitions for identifying suspected hepatitis E. It remains unclear to what extent the inclusion of symptoms other than acute jaundice syndrome improves specificity and whether any signs/symptoms can consistently distinguish AJS with and without HEV across settings. Here, we leverage data from facility-based acute jaundice surveillance in South Sudan (predominantly outpatients) and Bangladesh (inpatients) to (i) evaluate and compare the sensitivity and specificity of international case definitions for identifying suspected hepatitis E compared to laboratory-confirmed hepatitis E and explore if there are alternative case definitions with improved specificity across settings. Materials & Methods Surveillance site: South Sudan In March 2022, the South Sudan Ministry of Health, in partnership with Médecins Sans Frontières (MSF), implemented a reactive vaccination campaign against hepatitis E (HEV239; Hecolin; Innovax, Xiamen, China) in response to an outbreak in Bentiu internally displaced persons camp, South Sudan ( 20 ), coupled with a vaccine effectiveness study. As part of the study, MSF conducted comprehensive diagnostic testing for all patients with AJS identified at the MSF facility located in the camp ( 3 ). AJS was defined as the acute (recent, new, or sudden) onset of yellow coloration of the whites of the eyes or skin, dark urine, or pale clay stools. All cases of AJS were considered suspected cases of hepatitis E. All suspected hepatitis E cases seeking care at the MSF hospital (outpatient and inpatient departments) were identified by clinicians and referred to the study team after consultation or hospital admission. Study staff explained the study objectives and, among suspected cases willing to participate, obtained consent for participation. Adults provided written informed consent, while individuals under 18 years of age provided assent, and their guardians provided written informed consent. Study staff administered a questionnaire on demographics, vaccination status, and signs and symptoms including symptoms of AJS. A laboratory technician collected a venous blood sample and prepared all specimens for testing, storage, and transport. Details on specimen storage and handling have been described elsewhere ( 3 ). Laboratory methods: South Sudan Testing for IgM ELISA was conducted in a reference laboratory at the University Hospitals of Geneva. We used WANTAI HEV-IgM ELISA and WANTAI HEV-IgG ELISA (WE-7196 and WE-7296, Beijing Wantai Biological Pharmacy Ent.) to detect HEV antibodies in venous plasma following the package insert. Surveillance site: Bangladesh Surveillance methods in Bangladesh have been previously described ( 6 ). Hospital-based acute jaundice surveillance was established in six tertiary hospitals (five government teaching hospitals and one private teaching hospital) located in five of the seven divisions in Bangladesh. Tertiary hospitals in Bangladesh generally serve severely ill patients, some of whom have been referred from lower-level hospitals in districts and sub-districts near the tertiary hospital. In each hospital, a physician working with a field assistant from the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) reviewed daily admission records in the obstetrics and gynecology ward, adult medicine ward, and intensive care unit to identify AJS in-patients at least 14 years of age. AJS was defined as a new onset of either yellow eyes or skin within the past 3 months and continuing on the day of admission. The physician in each hospital approached all eligible patients and sought consent from the patient, or their guardian in the case of severely ill patients, for study enrollment. Patients over 17 years of age provided written informed consent, while patients 14 to 17 years of age provided written assent, and their guardian provided written informed consent. The physician recorded each consenting patient’s illness history and relevant clinical information, completed a questionnaire on patient demographics, collected a 5 mL blood specimen for laboratory testing, and monitored patient vital status for the duration of hospitalization. The physician asked patients whether symptoms were present at any time during their illness and whether the symptom was continuing on the day of admission. Among patients who were discharged, field assistants called all enrolled patients 3 months post-discharge to ascertain vital status. If patients did not have a phone, field assistants visited their home for follow-up. Post-discharge follow-up was not possible for patients admitted after June 30, 2017, due to the end of the surveillance period on September 30, 2017. Laboratory methods: Bangladesh Field assistants centrifuged blood specimens on the day of sample collection and stored serum at the hospital in a liquid nitrogen dry shipper. Samples were transported to a laboratory in Dhaka every two weeks. Once at the laboratory in Dhaka, samples were kept in a freezer at - 80°C until testing. Samples were tested using WANTAI HEV-IgM ELISA and WANTAI HEV-IgG ELISA (WE-7196 and WE-7296, Beijing Wantai Biological Pharmacy Ent.) to detect HEV antibodies in serum following the package insert. Statistical analysis All analyses were conducted separately for data from South Sudan and Bangladesh. We defined confirmed hepatitis E infection across sites as the presence of anti-HEV IgM antibodies in serum detected by ELISA. In primary analyses, we excluded suspected cases under the age of 14 from South Sudan since only individuals aged 14 and above were eligible for inclusion in Bangladesh. We excluded suspected cases with jaundice onset more than 30 days before the clinic visit/hospitalization in both study populations to focus on more typical conceptions of acute disease. In primary analyses patients were considered to have a symptom if they reported experiencing it at any point during their illness, even if it was not present on the day of their clinic visit/admission. We first assessed the sensitivity and specificity of international case definitions for hepatitis E in the WHO hepatitis E outbreak toolbox ( 19 ) for identifying hepatitis E compared to laboratory confirmed hepatitis E (i.e., anti-HEV IgM detected by ELISA) and estimated 95% Wald confidence intervals. The WHO recommended case definition for suspected hepatitis E during outbreaks is anyone with either or both of the following: (i) discrete onset of an acute illness with symptoms of acute infectious disease (fever, malaise, or fatigue) and signs of liver damage (anorexia, nausea, jaundice, dark urine, or right upper quadrant tenderness); and/or (ii) raised alanine aminotransferase (ALT) levels more than ten times the upper limit of normal laboratory levels ( 19 ). Given our focus on suspected case definitions, we limited our evaluation to the symptom-based clinical criteria outlined in the WHO case definition, excluding laboratory findings. Médecins Sans Frontières (MSF) defines suspected hepatitis E as the recent onset of jaundice plus the presence of one or more of the following: malaise, anorexia, epigastric discomfort, or nausea ( 9 ). International Medical Corps (IMC) defines suspected hepatitis E as clinically detected jaundice and one or more of the following: malaise, loss of appetite, fever, abdominal pain, or joint pain ( 9 ). In both study settings, fatigue/drowsiness was used interchangeably with malaise. Epigastric discomfort and joint pain were only collected in South Sudan and therefore, weren’t considered when evaluating the MSF or IMC case definitions in Bangladesh. A summary of signs and symptoms included in each international case definition for suspected hepatitis E is provided in Table 1 and signs and symptoms collected in each study population is provided in Table 2 . View this table: View inline View popup Download powerpoint Table 1. Summary of signs and symptoms in international case definitions for suspected hepatitis E in the World Health Organization hepatitis E outbreak toolbox ( 19 ) View this table: View inline View popup Table 2. Summary of signs and symptoms collected in Bentiu, South Sudan and Bangladesh To provide an effective “upper bound” on how well signs and symptoms, when combined in any manner, could distinguish between AJS (as defined in each setting) with and without HEV, we used an ensemble of flexible classification models. We fit and combined results from four models – random forest, a generalized additive model, extreme gradient boosting, and lasso – using the SuperLearner package in R. We explored separate models to classify HEV positive AJS cases based on (i) signs and symptoms alone; (ii) signs and symptoms plus age, sex, and days since jaundice onset. Both models were run separately in each study population. We used 10-fold cross-validation to create the optimal weighted average of the models (i.e., the ensemble-learner) with larger weights given to models with lower cross-validated risk. We used leave-one-out cross-validation and the average ensemble-learner to estimate the area under the receiver operator characteristic curve (AUC) in each study population. We quantified uncertainty in AUC values using the 2.5 th and 97.5 th percentiles of 2,000 bootstrap samples drawn with replacement from the observed and predicted outcomes. Given a lack of standardized guidance on what is considered “acute” jaundice, in sensitivity analyses, we fit the ensemble learning model to the subset of jaundiced patients with jaundice onset within 14 days of the clinic visit. In sensitivity analyses we repeated the ensemble models among acute jaundice patients in Bangladesh classifying patients as having a symptom only if the symptom was present on the day of their clinic admission. To explore alternative case definitions, we estimated the sensitivity, specificity, positive and negative predictive values for all combinations of signs and symptoms in each study setting. To balance sensitivity and specificity, we only considered alternative case definitions that were informative (sensitivity + specificity > 1). We explored case definitions based on the presence of at least one symptom in addition to jaundice, as well as definitions requiring at least two symptoms, and selected the alternative case definition in each setting with the highest specificity. If multiple case definitions had the same specificity, we selected the case definition with the highest sensitivity. If sensitivity was also tied, we selected the case definition with the fewest signs/symptoms (e.g., itch/fatigue selected over itch/fatigue/nausea). We repeated analyses in a combined dataset including both study populations and explored alternative case definitions using combinations of signs and symptoms that were present in both datasets. We applied post-stratification weights to ensure each study population contributed 50% to the overall sample, regardless of the original study population size. In sensitivity analyses, we repeated analyses evaluating existing international case definitions for suspected hepatitis E and exploring alternative case definitions in children under the age of 14 in South Sudan. Code and the minimal dataset for all analyses are available at: https://github.com/HopkinsIDD/hev-case-defintion . Ethics Ethical approval for the parent study in South Sudan was obtained from the South Sudan Ministry of Health Research Ethics Board (RERB-MOH # 54/27/09/2022) and MSF (MSF ERB #2167). Ethical approval for the parent study in Bangladesh was obtained from the institutional review board of the icddr,b (Protocol # PR-14060). Results We identified 524 patients at least 14 years of age with acute jaundice in South Sudan (March to December 2022) and 1925 patients hospitalized with acute jaundice in Bangladesh (December 2014 to September 2017). We excluded 68 patients in South Sudan and 280 patients in Bangladesh missing jaundice onset date or with jaundice onset more than 30 days of clinic visit or hospital admission and excluded 35 patients in South Sudan and 20 patients in Bangladesh with incomplete diagnostic test results and/or symptom history. Among patients with acute jaundice, 20% in South Sudan (83 of 421) and 38% in Bangladesh (611 of 1625) had IgM antibodies detected in serum by ELISA ( Table 3 ). In both study populations, a higher proportion of male suspected cases had IgM antibodies detected compared to females (26% versus 13% in South Sudan, 40% versus 32% in Bangladesh). Patients with acute jaundice in South Sudan had shorter delays to care seeking at the surveillance facility compared to Bangladesh (median 4 days versus 14 days; Supplemental Figure 1). Among patients with acute jaundice who were anti-HEV IgM negative at the time of their clinic visit, a substantially higher proportion had anti-HEV IgG detected by ELISA in South Sudan compared to Bangladesh (93% vs. 30%). In South Sudan, 9% of acute jaundice patients had malaria infection (39 of 421), 23% had evidence of acute or chronic hepatitis B infection (96 of 421), and 1% had hepatitis C infection (6 of 421) (Supplemental Table 1). Malaria and hepatitis C testing was not conducted in Bangladesh, and 8% of acute jaundice patients had acute hepatitis A infection (136 of 1625) and 34% had evidence of acute or chronic hepatitis B infection (555 of 1625). View this table: View inline View popup Table 3. Characteristics of patients with acute jaundice who presented to care at a health facility in Bentiu, South Sudan (March to December 2022) and were admitted to six tertiary hospitals in Bangladesh (December 2014 to September 2017) International case definitions for suspected hepatitis E The sensitivity and specificity of existing international case definitions varied by study population ( Table 4 ). The MSF case definition (AJS plus at least one of: fatigue/malaise, epigastric discomfort, nausea, anorexia/loss of appetite) had high sensitivity in both study populations (∼70-80%), but higher specificity in South Sudan (42%; 95% CI: 37, 47) compared to Bangladesh (17%; 95% CI: 15, 19). The IMC case definition (jaundice plus at least one of: fatigue/malaise, loss of appetite, fever, abdominal pain, joint pain) had the highest sensitivity and lowest specificity in both study populations. All international case definitions for suspected hepatitis E were misinformative in Bangladesh (sensitivity + specificity < 1), and the MSF case definition was the only informative case definition in South Sudan with specificity above 40%. The MSF and IMC case definitions had similar sensitivity and specificity in children under 14 years of age in South Sudan compared to older suspected cases, while the WHO case definition had higher sensitivity and lower specificity (Supplemental Table 4). View this table: View inline View popup Table 4. Sensitivity and specificity of international case definitions for suspected hepatitis E compared to laboratory-confirmed hepatitis E among patients with acute jaundice in South Sudan and Bangladesh Alternative case definitions for suspected hepatitis E Signs and symptoms alone had poor discrimination (AUC SouthSudan =0.64; 95% CI: 0.57, 0.71; AUC Bangladesh = 0.60; 95% CI: 0.57, 0.63) ( Figure 1 ) in both study populations. Ensemble-learning models including age, sex, and days since jaundice onset had improved but moderate ability to discriminate between uninfected and infected suspected cases (AUC SouthSudan = 0.74; 95% CI: 0.68, 0.80; AUC Bangladesh = 0.73; 95% CI: 0.71, 0.76) relative to symptoms alone. Results were similar when restricting analyses to suspected cases with AJS onset within 14 days of the clinic visit (Supplemental Figure 2). In sensitivity analyses discrimination was similar in patients with acute jaundice in Bangladesh based only on signs/symptoms at the time of hospital admission (AUC: 0.60; 95% CI: 0.57, 0.63) and signs and symptoms at the time of admission plus demographics (AUC=0.73; 95% CI: 0.71, 0.76) (Supplemental Figure 3). Discrimination was lower in patients with acute jaundice under 14 years of age in South Sudan compared to older patients with acute jaundice for signs and symptoms alone (AUC=0.54; 95% CI: 0.48, 0.60) and signs and symptoms plus demographics (AUC=0.60; 95% CI: 0.54, 0.66) (Supplemental Figure 4). Download figure Open in new tab Figure 1. Receiver operator characteristic curves for ensemble-learning models predicting hepatitis E infection in South Sudan (A) and Bangladesh (B). Demographic variables include age, sex, and days since jaundice onset. Bleeding, convulsions, and itch were excluded from ensemble-learning models in South Sudan due to low prevalence. Dashed line indicates discrimination no better than chance alone. Because ensemble models are impractical for real-world application and were intended only to represent an effective upper bound on potential performance, we next explored all combinations of signs/symptoms among patients with acute jaundice as alternative case definitions. Among the informative (sensitivity + specificity > 1) alternative case definitions with the highest specificity ( Table 5 ), all had higher specificity relative to existing case definitions. All alternative case definitions had sensitivity and specificity below 70% in South Sudan and below 60% in Bangladesh. Signs and symptoms in alternative case definitions with the highest specificity differed in each setting. In analyses combining study populations, no alternative case definitions had both sensitivity and specificity higher than 60% but alternative case definitions including abdominal pain and fatigue/malaise had a moderately high positive predictive value (77%; 95% CI: 74, 80). Case definitions requiring at least two symptoms had similar sensitivity and specificity as case definitions requiring at least one symptom. Among children under 14 in South Sudan, all alternative case definitions had sensitivity and specificity below 65% and had lower positive predictive values (65-69%) compared to alternative case definitions in older acute jaundice patients in South Sudan (88%) (Supplemental Table 5). View this table: View inline View popup Table 5. Sensitivity and specificity of informative alternative case definitions for suspected hepatitis E with the highest specificity compared to laboratory-confirmed hepatitis E in South Sudan and Bangladesh. Discussion Case definitions serve an important role not only in the clinical management of patients, but in assuring that surveillance data are interpretable and can shed light on disease burden. Existing international case definitions for suspected hepatitis E recommended by the WHO and NGOs had variable sensitivity (53-96%) and specificity (6-60%) compared to laboratory-confirmed hepatitis E across populations of patients with acute jaundice syndrome (AJS). While most existing suspected case definitions identified a substantial proportion of true hepatitis E cases, their ability to correctly identify negatives was often worse than chance alone. Alternative case definitions for suspected hepatitis E, including information on a broad range of signs and symptoms and demographics, had suboptimal ability to discriminate between AJS with and without hepatitis E, and no signs/symptoms consistently improved specificity across study populations. Given the limitations of signs and symptoms, broader access and use of rapid diagnostic tests for hepatitis E at the point-of-care can facilitate a better understanding of the true burden of hepatitis E and advocate for the timely use of existing interventions. Similar studies evaluating case definitions for other syndromically identified infectious diseases have had variable results. Among suspected cholera cases with acute watery diarrhoea in surveillance data from seven countries in the African Cholera Surveillance Network, adding signs/symptoms to the existing suspected case definition of acute watery diarrhoea improved specificity without a substantial decrease in sensitivity ( 21 ). In contrast, for Zika virus disease, international suspected case definitions that included rash in facility-based surveillance in Singapore had much higher specificity than those that didn’t, but also had much lower sensitivity ( 22 ). Though no alternative case definitions had both sensitivity and specificity higher than 60% in our combined study population, multiple alternatives had higher specificity than the current international case definitions for suspected hepatitis E (Supplemental Figure 5). These alternative case definitions for suspected hepatitis E could be considered for use in outbreak settings where rapid diagnostic tests (RDTs) are unavailable and where suspected case definitions with higher specificity may be preferred to inform outbreak response. The high negative predictive value of AJS plus abdominal pain or fatigue/malaise in our study population (77%, 95% CI: 74, 80), for example, could inform decision-making about whether to prioritize interventions best-suited to interrupt hepatitis E transmission (e.g. water and sanitation) over interventions better-suited for interrupting transmission of other pathogens. In contrast, the use of AJS alone as a case definition for suspected hepatitis E may be preferred in routine surveillance aimed at minimizing false negatives and understanding burden of disease or in settings with many competing causes of acute jaundice in which the prevalence of hepatitis E among acutely jaundiced patients may be lower (e.g. settings endemic for hepatitis E and other infectious causes of jaundice). Our findings support recent recommendations from the Viral Hepatitis Group at the European Society of Clinical Microbiology and Infectious Diseases, emphasizing the importance of point-of-care testing platforms using RDTs for HEV detection. While the focus of this paper was on older populations, the poor ability of signs and symptoms to discriminate between AJS with and without HEV in children under 14 years of age in South Sudan highlights the importance of confirmatory testing also among children. In 2022, the WHO Strategic Advisory Group of Experts on In Vitro Diagnostics (SAGE IVD) conditionally added RDTs for HEV to WHO’s list of essential in vitro diagnostics, noting that RDTs can aid diagnosis and surveillance of hepatitis E in settings where PCR and ELISA are not accessible, though additional information on test performance is needed ( 14 ). Although point-of-care tests for other infectious causes of acute jaundice, such as hepatitis A and malaria, are cheaper and more widely available than HEV RDTs, we identified frequent co-infections of hepatitis E with other infectious causes of acute jaundice (Supplemental Table 5) and illustrate how using diagnostic tests for other infectious diseases is not a viable strategy for ruling out hepatitis E infection in the absence of hepatitis E diagnostics. Current WHO recommendations for the recognition and investigation of hepatitis E outbreaks note that comprehensive testing for all suspected cases is not needed, but evidence-based guidance on the number of samples that should be tested and who should be prioritized for testing is lacking ( 9 ). Among the signs and symptoms evaluated in our study none were strong candidates for prioritizing acute jaundice patients for testing with RDTs. Our findings suggest that the use of signs and symptoms other than acute jaundice to determine who should be tested with RDTs would not meaningfully improve the positive predictive value of RDTs relative to acute jaundice alone. Our study populations differed in many ways, including different historical exposures to HEV, differences in the underlying incidence of other causes of jaundice, different definitions for acute jaundice syndrome (South Sudan: acute onset of yellow eyes or skin, dark urine, or pale clay stools; Bangladesh: new onset of either yellow eyes or skin within the past 3 months and continuing the day of admission), and most importantly, severity of cases. A majority of patients with acute jaundice in South Sudan were outpatients (93%), whereas all patients with acute jaundice in Bangladesh were hospitalized. The prevalence of some signs and symptoms differed between outpatients and inpatients in South Sudan (e.g. altered mental state, loss of appetite, vomiting; Supplemental Table 2), though the prevalence of these symptoms was sometimes more similar to Bangladesh among outpatients in South Sudan compared to inpatients (e.g. altered mental status). It is possible a combination of signs/symptoms that consistently improves specificity exists that improves specificity across study populations, but that we were unable to find this combination since not all signs/symptoms were collected in both study populations. We suspect misclassification of symptoms is most likely to be non-differential because all patients in our study populations were acutely jaundiced and ill, even if they were not infected with HEV, which could lead to underestimates of predictive accuracy. We were unable to evaluate the full WHO suspected case definition in either setting since no data were collected on tenderness in the upper right quadrant, or the MSF or IMC suspected case definitions in Bangladesh, since no data on joint pain or epigastric pain were collected in Bangladesh. All individuals in our study population had acute jaundice, therefore, the inclusion of data on tenderness in the upper right quadrant would not change our estimates of the sensitivity and specificity of the WHO suspected case definition. The inclusion of epigastric pain in the MSF case definition and joint pain in the IMC case definition in Bangladesh would likely improve sensitivity but lower specificity even further. We used ELISA to detect anti-HEV IgM, which has high sensitivity and specificity ( 13 , 23 ) but could miss infections among individuals seeking care shortly after infection if their IgM antibodies have not yet developed ( 24 ). Longer careseeking delays in Bangladesh (median delay: 14 days) likely minimize the likelihood of false negative ELISA results, but false negatives in South Sudan (median delay: 4 days) could have caused artificially lower estimates of sensitivity and specificity if misclassification occurred non-differentially by signs/symptoms. Despite this possibility, the sensitivity of IgM ELISA among all AJS cases identified in the South Sudan surveillance site was high among cases who sought care in the first 30 days since AJS onset (95%; Credible Interval: 93, 96), and only 4 AJS cases had detectable RNA but no detectable IgM based on ELISA ( 25 ). Conclusion Existing international case definitions for suspected hepatitis E had variable sensitivity and low specificity for identifying hepatitis E in acute jaundice surveillance in South Sudan and Bangladesh. Our findings demonstrate that modifying signs and symptoms included in case definitions for suspected hepatitis E is unlikely to meaningfully enhance understanding of the true burden of hepatitis E. Accurately distinguishing between AJS with and without HEV, requires expanded access to confirmatory diagnostic tests such as RDTs in low-income settings and strategic testing of patients with AJS. Investments in targeted studies to better define burden of disease with diagnostics in endemic countries could provide evidence on hepatitis E incidence that could inform evaluations of cost effectiveness of vaccination and other prevention measures. Data Availability Code and the minimal dataset for all analyses are available at: https://github.com/HopkinsIDD/hev-case-defintion . https://github.com/HopkinsIDD/hev-case-defintion Financial support The primary research in South Sudan was supported by Médecins Sans Frontières, and the funders of the study were fully involved in the study design, data collection, data analysis, data interpretation, and preparation of the manuscript. Support for some of the analyses of this manuscript was provided by the Gates Foundation (INV 145223). The research in Bangladesh was funded by the Centers for Disease Control and Prevention (CDC), USA, which had no role in study design, data collection, analysis, or preparation of the manuscript. Icddr,b is also grateful to the Government of Bangladesh, Canada, Sweden, and the UK for providing core/unrestricted support. Disclosures The authors have no conflicts of interest. Author contributions Conceptualization: AK, ASA, EG; Methodology: AK, ASA, EG, RCP, SPL; Formal analysis: AK, RCP; Investigation: KVA, RN, CA, RCP, AN, AA; Resources: KVA, RN; Data curation: KVA, CA, RCP, AN, KCB, SAS; Writing – Original Draft: AK, RCP; Writing – Review & Editing: CA, EG, JW, MH, MA, EG, ESG, FBL, DB, MR, JR, IC, IE, ASA, RCP, AN, KCB, SAS, KKP, AA, SU, SPL; Supervision: ASA, ESG, RCP; Project administration: RN, KVA, CA, EG, MA, RCP, AN, KCB, KKP, SU. Acknowledgements We thank all the MSF and icddr,b staff who collected these data and the participants in South Sudan and Bangladesh. We thank the diagnostic laboratories of the University Hospitals of Geneva for help with serological testing. References 1. ↵ Azman AS , Ciglenecki I , Wamala JF , Lynch J , Aggarwal R , Rahman M , et al. 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Diagnostic accuracy of hepatitis E virus antibody tests: A comprehensive meta-analysis . Hepatology Research . 2025 ; 55 ( 3 ): 346 – 62 . OpenUrl PubMed 24. ↵ Dalton HR , Bendall R , Ijaz S , Banks M . Hepatitis E: an emerging infection in developed countries . The Lancet Infectious Diseases . 2008 Nov 1; 8 ( 11 ): 698 – 709 . OpenUrl CrossRef PubMed Web of Science 25. ↵ Diagnostic performance and kinetics of hepatitis E viral RNA and IgM antibody test positivity in a genotype 1 outbreak in South Sudan | medRxiv [Internet] . [cited 2025 Jun 19]. Available from: https://www.medrxiv.org/content/10.1101/2025.04.03.25325193v1 View the discussion thread. Back to top Previous Next Posted October 06, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. 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