IMPROVING DIARRHOEA ESTIMATES

Instituto de Investigación Nutricional, Lima, Perú

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IMPROVING DIARRHOEA ESTIMATES

Claudio F. Lanata, M.D., M.P.H. Walter Mendoza, M.D.

Instituto de Investigación Nutricional A.P. 18-0191, Lima-18

PERU

Advisor: Robert E. Black, M.D., M.P.H.

Chairman Department of International Health School of Hygiene and Public Health

Johns Hopkins University, Baltimore, MD, USA.

Presented to:

Monitoring and Evaluation Team Child and Adolescent Health and Development

World Health Organization Geneva, Switzerland.

October 2002


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1. INTRODUCTION Diarrhoeal diseases remain a leading cause of morbidity and mortality in the world, particularly in developing countries. WHO, UNICEF and other partners are interested in updating the previous reviews on total and cause-specific diarrhoea morbidity and mortality in the world, to best estimate the burden of diarrhoeal diseases for the world in the year 2000. In this study, we wanted to produce the following outcomes:

1. To produce a data base for each of the WHO regions and 14 sub-regions, in the period 1990-2000, for children under 5 years of age, on the proportion of diarrhoeal illness caused by each type of diarrhoeal pathogen, at the community and health facility level.

2. To apply these estimates to the current estimates of diarrhoea burden produced by the U. of Virginia team.

3. To compare the current burden with the last global burden of diseases exercise and discuss potential reasons for current trends.

4. To describe the methodology used, data availability and assumptions used in reaching these new estimates.

5. To provide recommendations on how these estimates could be improved, interpreted and used.

It is expected that this exercise will contribute to the discussion and assessment of the diarrhoea-attributable burden of disease and injury for the year 2000 done by WHO. We present in this report our final results, to help in its discussion and interpretation.

2. METHODOLOGY 2.1 Data Sources and Statistical Analysis A systematic literature review was been conducted in order to get both printed or web based articles from journals and other sources. Efforts have also been made to contact relevant clinicians and scientists to identify all other non-published studies and all relevant model inputs as well. Search algorithms and strategies has been developed for the literature review and printed literature has been retrieved from leading libraries in Public Health, whether by library loan or photocopying them. Keywords used to conduct the search included “diarrhea” (or “diarrhoea”), “diarrhea AND epidemiology”, “diarrhea AND etiology”, “diarrhea AND community”, and “diarrhea AND hospital”, for the period 1990-2002, inclusive (August). Copies of papers identified with cause-specific data on diarrheal diseases were reviewed.. Besides hand search was conducted from all available articles. The search engines to locate web based publications and/or references included the following: Freemedicalhournals: www.freemedicaljournals.com PubMed: www.ncbi.nlm.nih.gov/entrez/query.fcgi MedHunt: www.hon.ch/MedHunt Medexplorer: www.medexplorer.com Medscape: www.medscape.com Medical World Search: www.mwsearch.com 2.2 Inclusion and exclusion criteria


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All identified published papers in the period 1990-20021 (June) were systematically reviewed, using the following criteria.

Inclusion criteria: a) Community studies

• < 1 week in frequency of home visits or telephone contacts. • > 1 year of surveillance • All types of diarrhoea or only dysenteric illness (Classified accordingly) • Stool cultures taken, even only for one enteropathogen. • Population under study < 5 yo.

b) Hospital or health facility-based Studies • > 1 year of surveillance • All diarrhoea cases studied or those selected by systematic sampling • Population under study < 5 yo

Exclusion Criteria:

• Outbreaks • Studies in day care centres or similar • Studies of special populations (nursing homes, etc) • Only on AIDS patients • Not definition of surveillance frequency or sampling scheme • Nosocomial infections

2.3 Data Base A data base on SPSS 11.0 was created including the above data, besides the following variables:

• Authors’ last name and initials • Journal reference • Year of publication • Year of study onset • Duration of follow-up (in months completed) • Type of study

o 1 = community based, o 2 = health services or hospital-based o 3 = day care centres (or similar) o 4 = Outbreaks o 5 = other types

• Description of type of study (written description) • Diarrhoea definition

o 1 = acceptable (3 or 4 liquid or semi liquid stools /24 h, or mother’s report) o 2 = not acceptable (others, excluding dysentery)

1 For most regions there was at least one available article, but for those which didn’t fulfill this condition we went further back to consider studies published before 1990 and after 1985. With this criterion AfroD and AfroE presented at least one study per setting, while other regions (EuroB and EuroC) didn’t have available information for community and/or outpatient studies.


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• Dysenteric illness definition o 1 = acceptable (one or more bloody stools ) o 2 = unacceptable (only mucus mixed with stools, others) o 9 = Not provided, unknown.

• Description of definition of diarrhoea or dysentery (written description) • Paper selected for review?

o 1 = Yes o 2 = No

• Country • WHO Region (use codes, 1-14) • Number of subjects studied (or No. stool samples or No. of persons-year studied) • Age group • Male:Female ratio • Number of males/Number of females • Description of Cohort characteristics and age (descriptive information) • Description of surveillance frequency, recall period, selection, etc (descriptive

information) • Type of stool sample studied:

o 1 = fresh stools o 2 = rectal swabs o 3 = both

• Description of timing of stool sampling, transport media used, time period until plates were inoculated, etc. (descriptive information)

• Stool microbiologic methods appropriateness? (samples inoculated into transport media and into plates within 24 h of being passed, laboratory methods acceptable. See methods below)

o 1 = Yes o 2 = No o 9 = unable to classify, lack of information on paper.

• Number of coinfected samples/number of samples tested • Percentage of coinfection

Since frequently more than one enteropathogen is present causing diarrhoea, we considered mixed infections whenever the data were reported.

• Salmonella (excluding S. typhi, treating all other types of Salmonella as one) o % positive (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested o Describe the types of Salmonella isolated (descriptive information)

• Shigella (all types) o % positive, any type (0 means not isolated, 99 not reported) o % positive Shigella dysenteriae (0 means not isolated, 99 means not

reported) o number of positive samples o % positive Shigella flexneri (0 means not isolated, 99 means not reported) o number of positive samples o % positive Shigella boydii (0 means not isolated, 99 means not reported) o number of positive samples


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o % positive Shigella sonei (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for any Shigella o Describe the methods for Shigella identification (descriptive information)

• Campylobacter o % positive (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested o Describe the methods for Campylobacter isolation (descriptive

information) • Vibrios

o % positive, any type (0 means not isolated, 99 not reported) o % positive Vibrio cholerae O1 (0 means not isolated, 99 means not

reported) o number of positive samples o % positive Vibrio cholerae O139 (0 means not isolated, 99 means not

reported) o number of positive samples o number of stool samples tested for any Vibrio o Describe the methods for Vibrio identificartion (descriptive information)

• ETEC o % positive, any type (0 means not isolated, 99 not reported) o % positive ETEC ST only (0 means not isolated, 99 means not reported) o number of positive samples o % positive ETEC LT only (0 means not isolated, 99 means not reported) o number of positive samples o % positive ETEC ST/LT only (0 means not isolated, 99 means not

reported) o number of positive samples o number of stool samples tested for any ETEC o Describe the methods for ETEC identification (descriptive information)

• EPEC o % positive EPEC (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for any EPEC o Describe the methods for EPEC identification (descriptive information)

• Rotavirus o % positive Rotavirus (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for Rotavirus o Describe the methods for Rotavirus identification (descriptive information)

• Giardia lamblia o % positive Giardia (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for Giardia o Describe the methods for Giardia identification (descriptive information)

• Cryptosporidium sp. o % positive Cryptosporidium (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for Cryptosporidium


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o Describe the methods for Cryptosporidium identification (descriptive information)

• Entamoeba hystolitica (for dysenteric illness only) o % positive E. hystolitica (0 means not isolated, 99 means not reported) o number of positive samples o number of stool samples tested for E. hystolitica in dysenteric cases o Describe the methods for E. hystolitica identification (descriptive

information) As a reference, the following laboratory methods (or acceptable variations that were discussed individually) were considered acceptable, although it was not used as an inclusion or exclusion criteria since not all papers provided detailed laboratory methods information.

• Salmonella/Shigella: SS, XLD, BSA,Hectoen, Selenite enrichment for salmonella. • Campylobacter: transport media with antibiotics (Skirrow´s supplement). Blood

agar (5% sheep blood) with Butzler supplement. Cultivated at 42C and with low oxigen tension or anaerobic chamber

• Vibrios: alkaline peptone water enrichment and subculture at 8 hs into TCBS agar • E coli: MacConkey agar, • ETEC: sondas DNA, cell cultures (Y1, cho cells), ileac loop, mouse model, • EPEC: Hep 2 cell cultures (diffuse, localized, auto aggregative). DNA probes for

EAF plasmid and other plasmids. • Rotavirus: ELISA. Electronic microscopy. • Giardia: MIF, SAF transport media, direct or zinc sulphate concentration. ELISA. • Crypto: MIF, SAF transport media. Modified Ziel Nielsen stain. • Entamoeba hystolitica: MIF, SAF transport media. Direct exam.

Data was entered into the data base for all articles reviewed up to the variable where the decision for inclusion or not into this review was taken. For papers not selected for the review, no further data was entered into the data base. 2.4 Data Analysis Papers selected for the review, satisfying all inclusion criteria and not having any exclusion criteria, were selected from the data base and grouped into two categories:

• Community-based studies • Health-facility studies (separately inpatients and outpatients)

For each of these groups, median percentages and 25% and 75% percentiles were calculated for each pathogen, for children 0-4 years of age. Those papers that provided narrower age groups were treated together with those that provided data for 0-4 yrs of age children.

2.5 Proposed Models

Based on the review of the data available, and after reviewing the natural history of diarrhoeal diseases, we considered a simple model to estimate the burden of diarrhoea, with the components described below. To construct it, we combined information obtained from the literature review, with demographic and health service utilization data available from other


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sources, most importantly the Demographic and Health Surveys (DHS) conducted worldwide with support from USAID; the Multiple Indicator Cluster Survey (MICS) conducted by Unicef; and other surveys conducted by the CDC, World Bank, Ministries of Health and other national or regional studies provided they all are using the same operational definition. Else, if other regional estimations (incidence, proportion missing in a few regions, and under five mortality rate due to diarrhoea) were needed to complete our data they will be estimated. In doing so, the components and sources to obtain the needed information would be:

1. Number of diarrhoeal disease episodes in children <5 years of age: This is the burden of diarrhoeal episodes at global and regional level. The estimate will be obtained from literature review, applying the median estimate of the incidence rate of diarrhoea obtained from community-based cohort studies2 to the 2000 population of children <5 years of age for the world and for the regions. Whenever the information is missing at regional level it will be estimated modelling known risk factors;

2. Number of diarrhoeal episodes attributable to diarrhoea in children <5 years of age in community: The median proportion of each aetiology of diarrhoeal disease estimated from community-based cohort studies from the literature review for the world and WHO regions will be used and applied to the number of diarrhoeal episodes estimated above;

3. Number of diarrhoeal episodes attributable to enteropathogens seen in outpatient facilities in children <5 years of age: We estimated the number of diarrhoeal episodes seen in outpatient services globally and in each WHO region. Since this information may have important variations amongst countries, even within the same region, we propose to use DHS, MICS and other data to estimate this figure. We will use the proportion of children with diarrhoea in the last two weeks that were seen in health facilities. Though this estimate has seasonal variations, we will apply that percentage to the total number of diarrhoeal estimates obtained above to estimate the number of diarrhoeal episodes seen in health facilities or by private doctors globally and in each region. We then will apply the median proportion of each enterpathogen in diarrhoea cases seen in outpatient facilities globally and on the WHO region, based on our literature review, to estimate the number of specific diarrhoeal episodes seen in outpatient facilities in each level;

4. Number of inpatients seen due to specific aetiologies: We will follow a similar approach as for outpatients, further explained next;

Community cases: Susceptibles Diarrhoea cases Specific cases by enteropathogen 2 From Kosek et al. The magnitude of the global burden of diarrheal disease in the year 2001. Bull WHO (in press), and from our own search.

Incidence of diarrhoea

Proportion in community

Risk factors


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Where: Pop<5: Population 0 – 4 yo; Incidence: Incidence of diarrrhoea; PropComm: Median proportion of each enteropathogen seen in community cohort studies; Outpatient cases: Susceptibles

Where: Pop<5: Population 0 – 4 yo; Incidence: Incidence of diarrhoea; HealServ: Global/Regional percentage of diarrhoea cases seeking for health services; PropOutpat: Median proportion of specific aetiologic agents seen in outpatients; Inpatient cases: Susceptibles

Where: Pop<5: Population 0 – 4 yo; Incidence: Incidence of diarrhoea; Admitted: Global/Regional percentage of diarrhoea cases admitted; PropInpat: Median proportion of specific aetiologic agents seen in inpatients; However, as there are few studies reporting the proportion of children being admitted, we suggest using of the proportion of specific aetiologic cases seen in inpatients as a proxy of the proportion of deaths due to these specific aetiologies, as our assumption is that the most


Proportion seeking care

Diarrhoea cases in outpatients

Diarrhoea cases

Proportion positive

Specific cases in outpatients

Cases = Pop<5*Incidence*HealServ*PropOutpat

Community Cases = Pop<5*Incidence*PropComm

Risk factors


Proportion admitted

Diarrhoea cases in intpatients

Diarrhoea cases

Proportion positive

Specific cases in inpatients

Cases = Pop<5*Incidence*Admitted*PropInpat

Risk factors


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severe cases get admitted. In so doing, in this report we will advance only to estimate the said proportion of specific aetiologies. This said specific proportion could be further used by us as a proxy of deaths by aetiology once the CHERG releases its new estimation of the annual number of deaths by diarrhoea in <5 yo. So, whilst the expected number of annual deaths to be estimated by the CHERG becomes available, our inpatient model becomes more simple: Susceptibles

According to the above formulae global figures can be readily estimated, but since in some regions some information is missing (incidence, specific proportions in any setting, service use), new estimations based on modelling known risk factors for enteropathogens causing diarrhoea might be calculated to fill the said gaps. 2.6 Population

Table 2. Estimated under five years old world population for year 2000

WHO Region population

AfroD 48,432,770 AfroE 57,195,691 AmroA 21,585,736 AmroB 44,814,382 AmroD 9,381,213 EmroB 16,421,557 EmroD 53,344,704 EuroA 21,535,945 EuroB 17,946,351 EuroC 12,475,780 SearoB 28,408,345 SearoD 140,336,521 WproA 8,070,921 WproB 124,981,979 Total 604,931,894

Source: WHO 3. Results 3.1 Global estimations

3.1.1 Articles selected

Search of the literature yielded 266 studies from 239 papers that met the inclusion criteria and none of the exclusion criteria, published in the period under study, with data on the proportion of diarrhoea due to any of the relevant enteropathogens. These articles represent at least one study in at least one of the three settings in 69 countries (36% of 191 countries), and are listed

Risk factors

Specific proportion positive hospitalized

Specific deaths by aetiolgy

Annual diarrhoea

deaths This Report


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in the Annex. In some we found that studies and/or results were published in more than one article. In such cases, the paper containing more relevant data (more detailed description, more pathogens reported, etc) is included in this list. Review papers or multicenter studies may contain data from more than one study and/or country, while some papers might also include more than one setting.

Diagram 1. Selection process of studies for estimations

Table 3. WHO Regions and countries with articles selected for any enteropathogen

WHO region Country Inpatients Outpatients Community TOTAL

Algeria 1 1 Cameroon 1 1 Gambia 1 1 Ghana 1 1 2 Guinea-Bissau 4 4 Madagascar 1 1 Nigeria 8 8

AfroD Total 1 11 6 18

Central African Republic 3 3 Ethiopia 1 1 Kenya 1 3 1 5 South Africa 5 1 1 7 Zambia 1 1 Zimbabwe 1 1

AfroE

Total 7 6 5 18 USA 3 4 5 12 AmroA Total 3 4 5 12 Argentina 4 3 1 8 AmroB Brazil 10 7 6 23

5,400 potential relevant citations in

electronic search

About 3,200 references excluded

2,200 studies for evaluation

Excluded 15 due to language

(600 + 150) studies + e-mail + hand search

1,600 studies excluded

266 selected studies (107 + 98 + 61), from 239 papers


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Chile 3 3 1 7 Honduras 1 1 Mexico 2 6 8 Paraguay 1 1 2 Uruguay 1 1 Venezuela 1 7 1 9 Total 20 23 16 59 Guatemala 1 2 3 Nicaragua 1 1 Peru 8 1 4 13 AmroD

Total 9 1 7 17 Bahrain 1 1 2 Iran 1 1 Jordan 1 1 2 Kuwait 2 2 Saudi Arabia 2 1 3 Tunisia 2 2

EmroB

Total 7 5 12 Egypt 1 3 4 8 Pakistan 1 2 3 Somalia 1 1 Yemen 1 1

EmroD

Total 3 6 4 13 Denmark 1 1 Finland 1 5 6 France 1 1 2 Germany 1 1 Greece 1 1 Ireland 1 1 Israel 1 1 2 4 Italy 1 1 Netherlands 1 1 Spain 1 1 2 Switzerland 1 1 United Kingdom 2 3 5

EuroA

Total 10 9 7 26 Albania 2 2 Poland 3 3 Romania 3 3 6 EuroB

Total 8 3 11 Hungary 2 2 Russia 1 1 EuroC Total 3 3 Indonesia 3 1 4 Thailand 5 2 7 SearoB Total 3 6 2 11 Bangladesh 6 9 1 16 India 12 6 4 22 Myanmar 1 1 Nepal 2 2

SearoD

Total 18 18 5 41 Australia 4 2 2 8 Japan 1 1 New Zeland 1 1 Singapore 2 2

WproA

Total 8 2 2 12 China 2 1 1 4 WproB Hong Kong 1 1


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Korea 2 2 Lao PDR 1 1 Malaysia 1 1 Papua New Guinea 1 1 Vietnam 1 2 3 Total 7 4 2 13

TOTAL 107 98 61 266 3.2 Proportion an number of global cases per setting Table 4 shows the global aetiological median percentages across settings, with their respective inter quartile range. In this and following tables we present data for both coinfection and unknown cases. However, these latter figures should be interpreted cautiously, as not all studies provided data of coinfection, nor it was uniformly presented, for in some cases it considered only “coinfection”, while in other cases it described the aetiologies. So, the global and regional estimations are just medians from available studies whenever the data was available. Unknown cases were estimated from the difference to 100% of all other single aetiologies and coinfections. Also note that it’s also provided the male:female ratio for each type of study.

Table 4. Global aetiological percentages across settings

Community Outpatient Inpatient Agents Median Iq range Median Iq range Median Iq range Salmonella 0.9 0.2 – 3.1 3.2 1.2 – 6.7 4.4 2.9 – 8.7 Shigella sp. 4.6 2.2 – 7.6 5.8 2.4 – 11.0 5.6 2.8 – 10.4 Campylobacter 7.6 3.9 – 13.4 12.6 4.0 – 16.7 4.5 2.3 – 9.9 Vibrio cholerae 0.5 0.3 – 2.4 1.5 0.0 – 3.0 2.1 0.0 – 15.6 ETEC 14.1 6.7 – 22.6 8.7 5.2 – 15.3 9.5 6.4 – 16.1 EPEC 8.8 6.6 – 13.2 9.1 4.5 – 19.4 15.6 8.3 – 27.5 Rotavirus 8 4.2 – 15.3 18 13.3 – 30.7 25.4 17.0 – 37.7 Giardia 10.2 7.4 – 18.8 3.0 1.2 – 5.7 1.6 0.5 – 5.5 Crytosporidium 5.7 3.8 – 8.8 2.5 0.8 – 4.0 3.4 1.2 – 7.8 Entamoeba 3.5 0.8 – 5.8 0.6 0.1 – 1.4 0.7 0.1 – 3.6 Coinfection 10.8 6.4 – 22.7 12.0 5.3 – 19.3 12.1 8.0 – 19.7 Unknown 25.4 N.E.* 23.0 N.E. 13.2 N.E. Male:Female 1.2 1.4 1.4

*N.E. Not estimated

With the global median we estimated the global number of community cases, as proposed by our model. From each aetiological proportion we estimated the number of cases due to that specific aetiology, and from their difference from the global number we calculated those non-specified or unknown aetiologies.

Table 5. Global aetiological cases (from medians) across settings

Agents Community Outpatients

Salmonella 17’422,039 20’533,615 Shigella sp. 89’045,975 37’275,419 Campylobacter 146’151,546 80’656,295 Vibrio cholarae 11’614,692 10’282,874 ETEC 272’945,271 55’913,129 EPEC 170’348,721 58’483,848


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Rotavirus 154’862,565 115’682,336 Giardia 196’481,879 19’280,389 Crytosporidium 110’339,577 16’131,259 Entamoeba 67’752,372 3’856,078 Coinfection 208’096,572 76’800,217 Unknown 491’688,643 147’816,318

3.2.1 Number of diarrhoeal episodes at the community level by cause for the year 2000

in children 0-4 years of age As indicated above we applied the median incidence of diarrhoeal diseases estimated from community-based epidemiological studies (3.2 episodes/child-year) estimated by Kosek et al and from our own revision for the year 2000 to the population of children 0-4 years of age for the year 2000 in the world (604’931,894 million) to obtain the estimated global number of diarrhoeal diseases episodes for the year 2000. To obtain an estimated number of diarrhoeal disease episodes caused by each selected enteropathogen, we applied the median percentage for each pathogen obtained from our review of community-based etiological studies to the global number of diarrhoeal episodes. We also applied the 25th percentile percentage to obtain a lower estimate and the same was done with the 75th percentile for an upper estimate.

Graph 1. Estimated global share of community cases, as of year 2,000 in <5 yo

3.2.2 Number of diarrhoeal episodes at health facilities by cause for the year 2000 in

children 0-4 years of age. To obtain an estimated number of diarrhoeal disease episodes seen in health facilities, by cause, we obtained the median percentage estimate of diarrhoeal episodes seen in health facilities from national surveys done by the Demographic and Health Surveys (DHS) program of USAID and Macro International Inc. worldwide, Multiple Indicator Cluster Survey (MICS)

Unknown25.4%

EPEC8.8%

Rotavirus 8.0%

Giardia10.1%

ETEC14.1%

Vibrio cholerae 010.6%

Cryptostoridium5.7%

Campylobacter7.5%

Shigella sp. 4.6%

Salmonella0.9%

Entamoeba 3.2%

Coinfection10.7%


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conducted by UNICEF, and other regional or national specific surveys conducted by CDC or Ministries of Health. In those surveys, the percentage of diarrhoeal episodes that occurred in children under 5 years of age in the two weeks prior to the survey that were seen in health facilities (without any classification into outpatient and inpatient facilities) is given. Assuming that seasonality is not affecting this estimate, and knowing that several regions of the world are missing, since those surveys are only done in developing countries, we have applied this percentage to the estimated number of diarrhoeal episodes at the community level to obtain an estimated number of episodes seen in health facilities as outpatients. To that number we applied the median proportion of diarrhoeal episodes attributable to each cause from outpatient studies, assuming that the outpatient studies provide a better representation of these surveys’ data are showing, than inpatient studies.

The same approach was used to estimate regional numbers, but as health service use was not available from above mentioned surveys and selected studies, additional bibliographic search was conducted to estimate the regional share of patients taken to health facilities due to diarrhoea. In regions where no information was available we had to model them, by regressing variables more correlated, to predict an estimated figure.

Graph 2. Estimated global share of outpatient cases, as of year 2,000 in <5 yo

3.2.3 Proportion of diarrhoeal inpatients by cause for the year 2000 in children 0-4

years of age We estimated the quartiles of the proportion of each aetiology of all the inpatient studies conducted in under 5 yo, as explained in the methods section, and the global median estimation is presented next.

Unknown23.0%

Salmonella3.2%

Shigella sp. 5.8%

Campylobacter12.6%

Vibrio cholerae 011.6%ETEC

8.7%

EPEC9.1%

Rotavirus 18.0%

Coinfection12.0%Entamoeba

0.6%Cryptostoridium

2.5%Giardia

3.0%


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Graph 3. Estimated global share of inpatient cases, as of 2,000 in <5 yo

3.3 Regional estimations Table 3 show us the many available studies across regions, but that is not our unique purpose, as specific information of each pathogen is required in each of the 14 WHO regions and each of the three settings. Tables 6 through 16 shows us where at least one study was selected in each region.

Table 6. Salmonella studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 4 2 6 Afro E 2 1 3 6 Amro A 2 2 2 6 Amro B 6 7 5 18 Amro D 5 1 6 Emro B 6 2 8 Emro D 3 2 5 Euro A 3 4 2 9 Euro B 3 3 6 Euro C 1 1 Searo B 1 2 3 Searo D 5 6 2 13 Wpro A 4 1 2 7 Wpro B 2 1 1 4 42 34 22 98

Table 7. Shigella sp. studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 4 2 6 Afro E 2 1 2 5

Unknown13.2%

Salmonella4.4%

Shigella sp. 5.6%

Campylobacter4.5%

Vibrio cholerae 014.0%

ETEC9.5%

EPEC15.6%

Rotavirus 25.4%

Coinfection12.1%

Giardia1.6%

Entamoeba 1%

Cryptostoridium3.4%


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Amro A 2 2 2 6 Amro B 8 9 6 23 Amro D 7 1 2 10 Emro B 6 2 8 Emro D 3 3 1 7 Euro A 1 2 3 Euro B 3 3 6 Euro C 1 1 Searo B 1 2 3 Searo D 10 9 3 22 Wpro A 2 2 4 Wpro B 2 3 1 6 47 40 23 110

Table 8. Campylobacter studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 3 2 5 Afro E 2 2 3 7 Amro A 1 2 2 5 Amro B 4 6 4 14 Amro D 8 1 2 11 Emro B 5 2 7 Emro D 2 3 1 6 Euro A 2 4 1 7 Euro B 1 1 2 Searo B 1 2 3 Searo D 5 8 2 15 Wpro A 3 1 2 6 Wpro B 2 2 1 5 35 36 22 93

Table 9. Vibrio cholerae studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 1 1 2 Afro E 1 1 2 Amro A 1 2 1 4 Amro B 1 1 1 3 Amro D 4 1 1 6 Emro B 2 2 Emro D 2 2 Searo B 2 1 3 Searo D 6 8 2 16 Wpro A 2 2 Wpro B 1 1 16 19 8 43

Table 10. ETEC studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 2 2 4 Afro E 1 3 4 Amro A 1 2 2 5 Amro B 4 5 7 16 Amro D 6 1 2 9 Emro B 4 4


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Emro D 2 3 3 8 Euro A 1 1 Euro B 2 2 4 Searo B 3 2 5 Searo D 4 10 2 16 Wpro A 2 2 Wpro B 1 2 1 4 25 31 26 82

Table 11. EPEC studies selected across WHO regions

TOTAL Afro D 3 2 5 Afro E 2 1 3 6 Amro B 9 7 7 23 Amro D 7 1 8 Emro B 6 2 8 Emro D 3 1 4 Euro A 1 1 1 3 Euro B 3 3 6 Searo B 2 2 Searo D 5 5 2 12 Wpro A 1 1 Wpro B 2 2 1 5 39 27 17 83

Table 12. Rotavirus studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 1 7 4 12 Afro E 7 5 5 17 Amro A 3 4 5 12 Amro B 16 17 9 42 Amro D 8 1 4 13 Emro B 6 4 10 Emro D 2 6 2 10 Euro A 10 9 6 25 Euro B 7 2 9 Euro C 3 3 Searo B 2 2 2 6 Searo D 13 12 4 29 Wpro A 7 2 2 11 Wpro B 7 3 2 12 92 74 45 211

Table 13. Giardia studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 4 4 Afro E 1 3 4 Amro B 4 2 6 12 Amro D 5 1 1 7 Emro B 3 3 6 Emro D 1 3 4 Euro A 2 2 Searo B 1 1 Searo D 5 6 2 13


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Wpro A 2 1 2 5 Wpro B 2 2 20 22 18 60

Table 14. Cryptosporidium studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 3 3 Afro E 1 1 Amro B 5 1 5 11 Amro D 7 1 2 10 Emro B 1 1 2 Euro A 1 1 2 Searo B 1 1 2 Searo D 5 3 2 10 Wpro A 2 2 Wpro B 1 1 21 8 15 44

Table 15. Entamoeba hystolitica studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 3 3 Afro E 1 2 3 Amro B 1 2 5 8 Amro D 2 2 Emro B 1 2 3 Emro D 2 2 4 Euro A 1 1 Searo D 6 7 3 16 Wpro B 1 2 3 13 17 13 43

Table 16. Coinfection studies selected across WHO regions

Inpatients Outpatients Community TOTAL Afro D 1 3 4 Afro E 1 1 Amro A 1 2 1 4 Amro B 5 4 3 12 Amro D 6 1 7 Emro B 5 1 6 Emro D 1 1 Euro A 1 1 Euro B 1 1 2 Searo B 1 1 2 Searo D 7 5 1 13 Wpro A 1 1 Wpro B 1 1 2 30 16 10 56

As we see some aetiologies were missing in some WHO regions. From a paper by Kosek et al3 and our own search we had available epidemiological data (chiefly incidence) for some regions, so in order to fill these gaps we conducted an additional literature search. Whenever

3 Kosek et al. The magnitude of the global burden of diarrheal disease in the year 2001. Bull WHO (in press).


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this search didn’t yield the required information, known risk factors for diarrhoea (log of per capita gross product, water sanitation, women illiteracy, under five mortality rate, human development index, breastfeeding, low birth weight, under weight --- % < -2 sd---, etc)4 were correlated with national or regional medians of the proportion of each enteropathogen causing diarrhoea per settting in countries and/or regions. Those with higher correlation were linearly regressed to predict missing values at regional or national level (and based on them the regional value was estimated).

Table 17. Missing information in regions

Who Region Community Outpatients Afro D -- -- Afro E -- -- Amro A Incidence Amro B -- -- Amro D -- -- Emro B -- -- Emro D -- -- Euro A Euro B Euro C

Incidence

Searo B -- -- Searo D -- -- Wpro A Incidence Wpro B -- --

Accordingly, next tables shows the steps we followed to complete missing information.

Table 18. Regional missing information and strategy to complete it

Indicator Community Outpatients Inpatients Incidence Literature search, regression N.A.

Health service use N.A.

Literature search, DHS, MICS, CDC, MoH, WB, other sources

N.A.

Specific aetiologies N.A. Regression N.A. Not applicable

Table 19. Criteria for selecting correlations and regression models

Correlation Regression

Pearson P value Collinearity (tolerance) P value

Higher values Significant at the 0.01 or 0.05 level (two tailed) >0.1 < 0.05

4 Latest available data from World Bank, DHS, MICS, WHO, CDC, Unicef, MoHs, etc.


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Next tables present the regressions we obtained following the above criteria to fill information missing in regions. Note that for each aetiology it’s indicated in how many out of the 14 WHO regions the information is missing.

Table 20. Regressions to complete regional information

Indicator Missing in regions Regression

Incidence 2/14 Incidence = 1.675 + 0.118*Womilit

Table 21. Regressions for regional estimations in community studies

Aetiology Missing Regression Salmonella 4/14 Shigella sp. 4/14 Campylobacter 4/14 Vibrio cholerae 8/14 ETEC 4/14 EPEC 7/14 EPEC = 4.886 + 0.88*Campy + (-0.108)*WomIllit Rotavirus 3/14 Rotavirus = 21.831 + (-0.83)*EPEC + (0.17)*WomIllit Giardia 8/14 Crytosporidium 8/14 Crypto = (-11.216) + 5.115*LogNPcap Entamoeba 9/14 Entamoeba = 1.353 + 0.8048*LowBW

WomIlit: Regional percentage of women who are illiterate LogNPcap: Log of the regional per capita of national product LowBW: Regional percentage of low birth weight

Table 22. Regressions for regional estimations in outpatient studies

Aetiology Missing Regression

Salmonella 2/14 Shigella sp. 2/14 Shigella = 50.512 + (-0.443)*RegSanit + (0.156)*WomIllit Campylobacter 1/14 Campy = 54.53 + (-0.481)*RegSanit Vibrio cholerae 5/14 Vibrio = 11.446 + (-0.11)*RegSanit ETEC 4/14 EPEC 4/14 Rotavirus -- -- Giardia 4/14 Crytosporidium 8/14 Crypto = 6.025 + 0.182*Rotavirus Entamoeba 9/14

RegSanit: Regional percentage of urban sanitation WomIlit: Regional percentage of Women illiteracy

Table 23. Regressions for regional estimations in inpatient studies

Aetiology Missing Regression Salmonella 2/14 Salmonella = 10.321 + (-0.216)*EPEC Shigella sp. 2/14 Shigella = 32.494 + (-0.299)*RegSanit Campylobacter 3/14 Vibrio cholerae 8/14 Vibrio = (-2.271) + 0.242*WonIllit


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ETEC 5/14 ETEC = 6.049 + 0.362*BreastFed + (-0.557)*LowBW EPEC 4/14 EPEC = 19.088 + 0.886*LowBW + (-0.55)*Rotavirus Rotavirus -- -- Giardia 7/14 Crytosporidium 7/14 Entamoeba 8/14 Entamoeba = (-28.746) + 10.389*LogNPcap RegSanit: Regional percentage of urban sanitation

WomIlit: Regional percentage of Women illiteracy BreastFed: Regional percentage of children exclusively breast fed in first 6 months

LowBW: Regional percentage of low birth weight LogNPcap: Log of the regional per capita of national product

In next tables we present the results of the medians of estimations for each aetiology for region, based on the literature review and from the regressions we presented above. Recall that tables 6 to16 allow us to identify each region where aetiological data couldn’t be found, while tables 20 to 23 deal with the modelling of regressions to fill those information gaps. The inter quartile range is not provided for aetiologies with only one selected study, nor for the estimations based on regressions. As noted in previous tables, in some regions we couldn’t model any regression for some aetiologies, whose implications will be discussed in further detail later on.

Table 24. AfroD median aetiological percentages across settings

Agents Community (Iq range)

Outpatients (Iq range)

Inpatients (Iq range)

Salmonella 2.3 (2.0 – 2.6) 1.3 (1 – 13.3) 6.2 Shigella sp. 14.5 (1.5 – 27.5) 1.7 (1.1 – 8.8) 8.6 Campylobacter 5.9 (3.1 – 8.7) 17.7 (7.7 – 30.5) 5.1 Vibrio cholerae 0.6 1.9 16.2 ETEC 8.5 (4.6 – 12.4) 1.2 (0.5 – 1.8) 19.1 EPEC 4.2 (3.8 – 4.6) 21.4 (1.2 – 24.0) Rotavirus 6.2 (3.5 – 24.9) 19.6 12.3 Giardia 15.1 (14.7 – 18.2) Crytosporidium 6.5 (5.7 – 7.7) 2.5 Entamoeba 4.1 (0.0 – 7.0) 1.5 Coinfection 15.8 (4.8 – 34.6) 19.6 Unknown 16.4 32.8 11.4

Table 25. AfroE median aetiological percentages across settings

Agents Community

(Iq range) Outpatients (Iq range)


Salmonella 1.9 (0.6 – 1.9) 7.4 2.5 (1.4 – 3.6) Shigella sp. 2.9 (2.0 – 3.8) 6.5 4.8 (3.6 – 6.0) Campylobacter 11.3 (3.5 – 11.7) 10.1 (4.8 – 15.3) 3.8 (2.2 – 5.3) Vibrio cholerae 0.3 0.5 1.4 ETEC 1.9 (1.6 – 3.1) 4.9 5.1 EPEC 8.8 (8.6 – 9.7) 8.8 21.6 (15.6 – 27.6) Rotavirus 9.8 (6.3 – 15.5) 23.5 (19.3 – 31.1) 24.3 (20.8 – 32.3) Giardia 6.4 (0.9 – 10.0) 4.9 Crytosporidium 2.5 1.7 Entamoeba 3.3 (0.3 – 6.3) 7.8 8.9 Coinfection 7.9 Unknown 43.0 23.9 27.6


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Table 26. AmroA median aetiological percentages across settings

Agents Community



Salmonella 1.7 (0.4 – 2.9) 0.9 (0.7 – 1.0) 1.4 (1.3 – 1.5) Shigella sp. 4.4 (1.3 – 7.4) 5.3 (4.2 – 6.4) 2.9 (0.4 – 5.3) Campylobacter 2.7 (0.3 – 5.1) 3.8 (3.6 – 3.9) 3.1 Vibrio cholerae 0.0 0.2 (0.0 – 0.3) 0.5 ETEC 9.9 (5.2 – 14.6) 6.4 (5.2 – 7.5) 13.8 EPEC 0.7 12.8 Rotavirus 8.3 (5.3 – 21.5) 10.6 (7.0 – 35.5) 23.7 (16.5 – 26.4) Giardia 9.2 Crytosporidium 13.8 4.1 Entamoeba 1.4 11.6 Coinfection 7.1 4.2 9.2 Unknown 50.2 35.6 21.1

Table 27. AmroB median aetiological percentages across settings




Salmonella 0.2 (0.0 – 2.4) 3.5 (2.0 – 4.0) 2.9 (1.1 – 3.2) Shigella sp. 3.1 (1.8 – 7.2) 6.8 (4.5 –10.6) 6.8 (2.9 – 7.7) Campylobacter 9.9 (2.5 – 16.4) 8.2 (2.3 – 15.4) 6.4 (1.1 – 9.5) Vibrio cholerae 0.3 0.0 0.4 ETEC 15.2 (13.3 – 34.8) 4.5 (3.5 – 11.8) 6.7 (1.8 – 18.4) EPEC 13 (6.6 – 17.9) 17.6 (10.0 – 33.3) 27.5 (17.1 – 34.2) Rotavirus 6 (4.5 – 15.5) 25.8 (15.0 – 33.8) 21 (12.6 – 42.4) Giardia 14.1 (9.0 – 20.0) 3.5 (1.9 – 5.0) 2.8 (0.5 – 15.0) Crytosporidium 8.5 (3.1 – 20.2) 0.7 7.2 (3.2 – 14.9) Entamoeba 1.7 (0.9 – 4.8) 0.8 (0.7 – 0.8) 12.1 Coinfection 11.1 (4.5 – 39.0) 11.0 (9.0 – 15.0) 8.5 Unknown 16.9 17.8

Table 28. AmroD median aetiological percentages across settings




Salmonella 0.1 0.8 (0.3 – 7.1) Shigella sp. 7.9 (5.9 – 9.8) 5.5 9.1 (4.0 – 10.7) Campylobacter 17.7 (12.1 – 23.2) 16.5 10.3 (8.2 – 14.6) Vibrio cholerae 2.9 0.0 1.7 (1.5 – 5.3) ETEC 38.3 (38.0 – 38.6) 13.9 20.3 (10.3 – 29.7) EPEC 18.5 11.0 (7.1 – 29.7) Rotavirus 4.2 (3.6 – 5.5) 35.4 25.0 (14.3 – 40.3) Giardia 29.3 1.6 7.0 (1.6 – 23.6) Crytosporidium 4.3 (3.2 – 5.4) 0.3 5.6 (0.9 – 9.5) Entamoeba 1.5 1.8 (0.0 – 3.5) Coinfection 16.8 18.8 Unknown 10.0


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Table 29. EmroB median aetiological percentages across settings

Agents Community



Salmonella 2.6 (2.0 – 3.2) 8.4 (5.8 – 14.7) Shigella sp. 0.2 (0.0 – 0.3) 4.1 (0.9 – 5.1) Campylobacter 1.4 (0.5 – 2.3) 2.3 (0.8 – 4.9) Vibrio cholerae 2.0 1.2 (0.0 – 2.3) ETEC 7.6 (6.0 – 14.7) EPEC 2.6 7.6 (3.2 – 11.9) 8.5 (5.8 – 16.4) Rotavirus 16.1 13.4 (6.9 – 30.6) 37.4 (28.0 – 44.4) Giardia 17.4 (1.4 – 30.0) 0.8 (0.0 – 1.6) Crytosporidium 8.0 4.1 1.5 Entamoeba 1.4 2.7 (0.3 – 5.0) 4.9 Coinfection 11.8 12.2 (6.2 – 14.2) Unknown 71.9 37.0 11.2

Table 30. EmroD median aetiological percentages across settings




Salmonella 2.9 (2.7 – 3.0) 6.8 (3.2 – 7.7) Shigella sp. 7.6 2.4 (1.8 – 6.0) 3.6 (0.7 – 6.8) Campylobacter 13.5 10.0 (2.3 – 16.8) 0.6 (0.5 – 0.7) Vibrio cholerae 2.1 (2.0 – 2.3) 8.9 ETEC 23.7 (19.9 – 51.6) 8.7 (3.8 – 17.0) 11.4 (8.7 – 14.0) EPEC 10.3 14.0 19.8 (9.5 – 43.2) Rotavirus 4.1 (3.8 – 4.3) 21.6 (13.9 – 40.5) 22.0 (9.6 –34.3) Giardia 5.0 (3.0 – 21.3) 1.2 Crytosporidium 4.5 2.1 Entamoeba 1.7 2.3 (0.6 – 3.9) Coinfection 2.4 Unknown 34.7 28.9 23.4

Table 31. EuroA median aetiological percentages across settings




Salmonella 0.4 (0.0 – 0.8) 11.7 (7.1 – 26.0) 11.9 (8.6 – 15.5) Shigella sp. 0.7 (0.6 – 0.8) 0.7 Campylobacter 11.8 (5.1 – 28.8) 8.8 (2.0 – 15.5) Vibrio cholerae 0.0 0.4 0.0 ETEC 2.2 EPEC 2.0 4.5 4.2 Rotavirus 23.3 (13.1 – 27.4) 17.2 (15.5 – 32.6) 30.7 (18.0 – 42.3) Giardia 4.2 (3.0 – 5.3) Crytosporidium 12.5 3.6 4.8 Entamoeba 1.4 0.0 11.8 Coinfection 9.0 Unknown 60.4 46.0 16.0


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Table 32. EuroB median aetiological percentages across settings

Agents Community



Salmonella 3.2 (1.1 – 15.3) 6.6 (4.2 – 23.2) Shigella sp. 8.5 (2.2 – 26.5) 5.9 (4.0 – 12.4) Campylobacter 6.5 4.5 Vibrio cholerae 0.4 0.0 ETEC 10.8 (6.4 – 15.3) 6.5 (6.2 – 6.8) EPEC 9.0 8.6 (4.7 – 19.4) 6.7 (4.0 – 13.2) Rotavirus 13.9 15.5 (10.5 – 20.5) 26.0 (18.6 – 32.7) Giardia 7.1 Crytosporidium 7.3 3.2 Entamoeba 1.4 10.2 Coinfection 3.0 12.5 Unknown 63.4 33.1 21.1

Table 33. EuroC median aetiological percentages across settings




Salmonella 9.3 Shigella sp. 6.1 19.2 Campylobacter 6.4 Vibrio cholerae 0.4 ETEC 1.6 EPEC 9.2 13.6 Rotavirus 14.1 22.1 (19.6 – 88.5) Giardia 7.2 Crytosporidium 6.5 2.4 Entamoeba 1.4 4.7 Coinfection Unknown 63.8 57.4 29.4

Table 34. SearoB median aetiological percentages across settings




Salmonella 8.5 (7.9 – 9.0) 12.3 8.4 Shigella sp. 6.7 (4.9 – 8.4) 12.6 5.3 Campylobacter 27.0 (8.7 – 45.3) 13.3 Vibrio cholerae 0.3 1.9 (0.8 – 3.0) 0.9 ETEC 12.3 (7.2 – 17.3) 9.1 (6.5 – 11.2) 20.1 EPEC 27.5 4.2 (2.8 – 5.5) 3.1 Rotavirus 7.2 (4.6 – 9.8) 19.4 (19.0 – 19.7) 41.3 (35.3 – 47.2) Giardia 2.0 Crytosporidium 5.3 1.8 3.4 Entamoeba 1.6 2.4 Coinfection 10.4 5.9 Unknown 17.6 15.1


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Table 35. SearoD median aetiological percentages across settings

Agents Community



Salmonella 0.6 (0.3 – 0.8) 1.4 (0.2 – 3.8) 4.2 (3.2 – 10.0) Shigella sp. 4.4 (3.6 – 5.4) 10.4 (3.2 – 19.9) 9.2 (4.2 – 12.2) Campylobacter 8.9 (4.0 – 13.8) 16.3 (12.8 – 26.7) 3.7 (3.2 – 14.7) Vibrio cholerae 2.2 (1.7 – 2.7) 3.7 (0.8 – 12.0) 11.7 (7.1 – 19.7) ETEC 13.3 (12.8 – 13.8) 15.3 (13.4 – 20.0) 9.7 (2.6 – 11.8) EPEC 9.1 (7.0 – 11.2) 9.0 (5.5 – 10.7) 21.1 (15.6 – 30.5) Rotavirus 11.6 (5.1 – 15.2) 17.9 (11.2 – 25.1) 20.8 (8.5 – 25.8) Giardia 5.6 (0.9 – 10.3) 1.9 (0.6 – 7.0) 1.6 (0.7 – 4.1) Crytosporidium 3.9 (3.8 – 4.0) 3.2 (1.1 – 11.9) 1.3 (1.0 – 2.7) Entamoeba 5.1 (0.9 – 5.5) 0.3 (0.1 – 0.6) 0.6 (0.5 – 1.4) Coinfection 18.8 19.9 (6.9 – 34.8) 11.7 (9.7 – 20.2) Unknown 16.6 0.7 4.4

Table 36. WproA median aetiological percentages across settings




Salmonella 16.7 (12.7 – 20.8) 3.5 4.4 (1.6 – 15.2) Shigella sp. 13.8 (4.6 – 22.9) 6.2 0.6 (0.4 – 0.7) Campylobacter 4.4 (4.2 – 4.6) 5.6 2.8 (1.7 – 3.1) Vibrio cholerae 0.4 0.0 (0.0 – 0.0) ETEC 13.3 (10.4 – 16.2) 2.3 EPEC 8.8 2.7 Rotavirus 4.5 (2.1 – 6.9) 12.0 (11.8 – 12.1) 27.1 (15.7 – 36.5) Giardia 7.5 (6.7 – 8.5) 0.8 0.8 (0.4 – 1.1) Crytosporidium 14.5 (8.1 – 20.8) 3.9 Entamoeba 1.4 18.3 Coinfection 4.1 Unknown 15.2 67.6 37.0

Table 37. WproB median aetiological percentages across settings




Salmonella 0.7 5.0 13.5 (3.7 – 23.3) Shigella sp. 3.5 15.4 (6.1 – 18.0) 6.8 (2.1 – 11.5) Campylobacter 4.9 11.9 (6.8 – 17.0) 8.5 (4.7 – 12.2) Vibrio cholerae ETEC 2.8 6.3 (6.0 – 6.5) 20.6 EPEC 7.0 25.9 (3.0 – 48.7) 8.8 (8.3 – 9.3) Rotavirus 8.0 (4.0 – 12.0) 50.0 (13.0 – 52.6) 56.0 (24.6 – 56.4) Giardia 0.8 (0.2 – 1.3) Crytosporidium 5.6 10.7 Entamoeba 1.5 0.7 (0.0 – 1.3) 3.8 Coinfection 23.0 Unknown 65.9


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In the following tables we present a ranking of all aetiologies in each setting across 14 WHO regions.

Table 38. Rank order of aetiologies in community studies across WHO regions

Agents AfroD AfroE AmroA AmroB AmroD EmroB EmroD EuroA EuroB EuroC SearoB SearoD WproA WproBSalmonella 11 10 8 12 10 6 5 12 1 8 Shigella sp. 4 8 6 9 5 5 7 9 4 6 Campylobacter 7 2 7 6 4 3 2 6 9 5 Vibrio cholerae 12 12 11 11 8 7 10 11 ETEC 5 11 3 2 1 2 3 3 5 EPEC 9 4 4 3 4 4 4 3 3 1 5 6 3 Rotavirus 8 3 4 8 7 2 7 2 2 2 6 4 8 2 Giardia 3 6 10 3 2 7 7 Crytosporidium 6 9 2 7 6 3 6 3 4 4 8 10 3 4 Entamoeba 10 7 9 10 9 5 8 5 5 5 9 8 10 7 Coinfection 2 6 5 5 4 1 Unknown 1 1 1 1 1 1 1 1 1 2 2 1

Table 39. Rank order of aetiologies in outpatient studies across WHO regions

Agents AfroD AfroE AmroA AmroB AmroD EmroB EmroD EuroA EuroB EuroC SearoB SearoD WproA WproB

Salmonella 8 6 9 8 8 7 4 8 5 10 6 6 Shigella sp. 7 7 5 6 6 11 8 8 5 4 4 5 3 3 Campylobacter 4 3 8 5 3 10 4 3 7 3 3 3 4 4 Vibrio cholerae 6 11 10 12 9 9 11 9 11 6 10 7 8 ETEC 9 8 4 7 4 5 3 6 4 5 EPEC 2 4 3 5 3 5 4 8 6 2 Rotavirus 3 2 2 1 1 3 2 2 2 1 2 2 1 Giardia 9 3 9 7 2 6 6 6 2 9 9 7 7 Crytosporidium 5 10 7 11 8 6 10 7 9 5 11 8 5 Entamoeba 5 10 7 9 10 12 8 Coinfection 6 4 2 4 10 7 1 Unknown 1 1 1 2 5 1 1 1 1 1 2 11 1

Table 40. Rank order of aetiologies in inpatient studies across WHO regions

Agents AfroD AfroE AmroA AmroB AmroD EmroB EmroD EuroA EuroB EuroC SearoB SearoD WproA WproB

Salmonella 7 8 9 9 11 5 6 3 6 5 4 8 4 4 Shigella sp. 6 6 8 6 6 8 7 10 8 3 5 6 10 8 Campylobacter 8 7 7 8 5 9 10 6 9 9 6 7 Vibrio cholerae 3 9 10 11 10 11 5 11 10 9 4 11 ETEC 2 5 3 7 2 6 4 9 7 7 2 5 8 3 EPEC 3 4 1 4 4 3 8 5 4 7 2 7 6 Rotavirus 4 2 1 2 1 1 2 1 1 2 1 1 2 1 Giardia 10 7 12 9 10 9 Crytosporidium 5 8 10 7 6 11 5 Entamoeba 9 4 5 3 9 7 4 4 6 8 12 3 Coinfection 1 6 4 3 2 8 5 3 3 5 2 Unknown 5 1 2 3 1 2 2 1 3 7 1

4. Discussion, issues to be addressed and next steps

The consistency of regional vs. global estimates: Although the difference might be explained not only by the scarcity of available studies in some regions, but also for to the wide regional inter-quartile range, biasing some estimates; it should be further discussed if a global estimation should only be the sum of all regions, rather than just a figure stemming from global parameters;


Page 27 of 48

On the aetiological agents considered: The fact that not only some regions are missing information on specific aetiological share causing diarrhoea in any of the three settings, but, also that there’s is still lack of evidence that some of the aetiologies we considered are proven causes of diarrhoea, may lead us to reconsider to continue including some of them;

On the availability of studies: Some regions/countries may be over-represented, somehow biasing the regional estimations, as not all regions/countries are epidemiologically homogenous. It might be worth discussing the convenience of considering at least two regions, as not them all are epidemiologicaly different;

Age groups under study: As any age grouping younger <5 yo was considered to be 0 – 4 yo, this might have biased some regional studies, not only because their scarcity, but also due to their epidemiology, which is not the same through these ages;

Misrepresentation of countries: Selected sites of study may not represent the country where it was conducted. Most likely investigators selected a particular area because diarrhoea was perceived to be a problem there. Besides, we didn’t distinguish rural from urban areas; The sensitivity and specificity of microbiological methods: We included only diagnoses done based on standard tests and procedures for each enteropathogen, whose different sensitivities and specificities were not considered in our estimations; Mixed infections: Each positive case was reported as present if counted as a single diarrhoeal episode and if alone. Not all studies provided this information, nor in all cases where coinfection is described this information is not uniformly presented;

On the estimates of diarrhoeal episodes seen in health facilities by cause: These figures should be taken cautiously, since empirical evidence suggests that the use of DHS, MICS and other estimates might be overestimated; No time trends considered: Though most studies haven’t been conducted in the last few years, we are assuming that the results of the studies remain steady; On the follow-up: Not all studies have a follow-up multiple of 12 months, which may introduce seasonality bias; No source of information of diarrhoeal deaths due to Rotavirus: Our assumption that the proportion of diarrhoeal episodes from inpatient studies, as being the most severe, may represent the proportion of diarrhoeal causes in children who died may be wrong; No nosocomial infections considered: Most of inpatient studies don’t present these data, but those that do, report some of them (e.g. rotavirus) as having an important epidemiological role with impact on costs and length of hospitalizations, so it’s worth discussing the convenience of its inclusion in further burden of diarrhoea estimations. This is one of the first efforts to estimate the burden of diarrhoeal diseases by aetiology at a global and regional level, and by categories of illness (diarrhoeal episodes seen at the community and in health facilities as well as diarrhoeal deaths). Several limitations exist in this study that limits its conclusions:


Page 28 of 48

1. The intention by WHO to use this information to produce country-specific estimates by aetiology may not be valid, given all the problems identified in this review.

Even though all these limitations exist, important conclusions could be taken from our results. These are some:

• This is the first attempt to produce global and regional estimates of cause-specific burden of diarrhoeal diseases.

• The estimates obtained have produced similar ranking of enteropathogens as the most

important causes of diarrhoeal cases in the community or diarrhoeal deaths than previous estimates. It reinforce the current knowledge that rotavirus, ETEC and EPEC represent the most important causes of severe diarrhoea worldwide, which should be given priority for vaccine development.

We have looked for previous studies to compare our results with previous burden estimates. There are only estimates produced for some pathogens, like rotavirus and Shigella, but not for all enteropathogens. Our results are similar with those previous attempts, suggesting that although the overall diarrhoea mortality is being reduced significantly since the 1980s, the burden of disease for these pathogens have not changed significantly, which is unlikely. There is a need to develop better methods and to conduct better studies to facilitate more precise burden estimates. ANNEX 1 PUBLICATIONS IN THE PERIOD 1990 – 2001 SELECTED FOR THIS REVIEW 1. Abu-Elyazeed R, Wierzba TF, Mourad AS, Persuki LF, Kay BA, Rao M, Churilla

AM, Bourgeois AL, Mortagy AK, Kamal SM, Savarino SJ, Campbell JR, Murphy JR, Naficy A, Clemens JD. Epidemiology of Enterotoxigenic Escherichia coli Diarrhea in a Pediatric Cohort in a Periurban Area of Lower Egypt. J Infect Dis 1999;179:382-389.

2. Agnew DG, Lima AAM, Newman RD, Wuhib T, Moore RD, Guerrant RL, Sears C.

Cryptosporidiosis in Northeastern Brazilian Children: Association with Increased Diarrhea Morbidity. J Infect Dis 1998;177:754-760.

3. Ahmed MU, Alam MM, Chowdhury NS, Haque MM, Shadid N, Kobayashi N,

Taniguchi K, Urasawa T, Urasawa S. Analysis of Human Rotavirus G Serotype in Bangladesh by Enzime-Linked Immunosorbent Assay and Polimerase Chain Reaction. J Diarrhoeal Dis Res 1999;17(1):22-27.

4. Akhter J, Sikotra S, Qadri SM Myint SH. Comparison of Paediatric Viral

Gastroenteritis at Large Medical Centres in Saudi Arabia and the United Kingdom. J Diarrhoeal Dis Res 1994;12(4):257-260.


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5. Akinyemi KO, Oyefolu AO, Opere B, Otunba-Payne VA, Oworu AO. Escherichia coli in patients with acute gastroenteritis in Lagos, Nigeria. East Afr Med J 1998; 75(9):512-515.

6. Alam NH, Faruque ASG, Dewan N, Sarker SA, Fuchs GJ. Characteristics of Children

Hospitalized with Severe Dehydration and Persistent Diarrhoea in Bangladesh. J Health Popul Nutr 2001;19(1):18-24.

7. Albert MJ, Faruque ASG, Faruque SM, Sack RB, Mahalanabis D. Case-Control Study

of Enteropathogens Associated with Childhood Diarrhea in Dhaka, Bangladesh. J Clin Microbiol 1999;37(11):3458-3464.

8. Al-Bwardy MAA, Ramia S, Al-Frayh AR, Chagla AH, Al-Omair AA, El-Hazmi

MAF, Lambourne A, Bahakim H, Salman H. Bacterial, parasitic and viral enteropathogens associated with diarrhoea in Saudi children. Ann Trop Paediatr 1988;8:26-30.

9. de Andrade JAB, de Oliveira JOT, Fagundes Neto U. Letalidade em crianças

hospitalizadas com diarréia aguda – fatores associados ao óbito. Rev Ass Med Brasil 1999;45(2):121-127.

10. Ardern-Holmes SL, Lennon D, Pinnock R, Nicholson R, Graham D, Teele D,

Schousboe M, Gillies M, Hollis B, Clarkin A-M, Lindeman J, Stewart J. Trends in hospitalization and mortality from rotavirus disease in New Zeland infants. Pediatr Infect Dis J 1999;18(7):614-619.

11. Arista S, Giovannelli L, Pistoia D, Cascio A, Parea M, Gerna G. Electropherotypes,

subgroups and serotypes of human Rotavirus strains causing gastroenteritis in infants and young children in Palermo, Italy, from 1985 to 1989. Res Virol 1990;141:435-448.

12. Armah GE, Mingle JAA, Dodoo AK, Anyanful A, Antwi R, Commey J, Nkrumah FK.

Seasonality of rotavirus infections in Ghana. Ann Trop Paediatr 1994;14:223-230. 13. Audu R, Omilabu SA, de Beer M, Peenze I, Steele AD. Diversity of Human Rotavirus

VP6, VP7, and VP4 in Lagos State, Nigeria. J Health Popul Nutr 2002;20(1):59-64. 14. Banajeh SM, Ba-oum NHS, Al-Sanabani RMN. Bacterial Aetiology and Anti-

Microbial Resistance of Childhood Diarrhoea in Yemen. J Trop Ped 2001;47:301-303. 15. Baqui AH, Sack RB, Black RE, Haider K, Hossain A, Alim ARM, Yunus M,

Chowdhury HR, Siddique AK. Enteropathogens Associated with Acute and Persistent Diarrhea in Bangladeshi Children <5 Years of Age. J Infect Dis 1992;166:792-796.

16. Baqui AH, Yunus MD, Zaman K, Mitra AK, Hossain KMB. Surveillance of patients

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