1. Epidemiology and Global Health
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Enteropathogen antibody dynamics and force of infection among children in low-resource settings

  1. Benjamin F Arnold  Is a corresponding author
  2. Diana L Martin
  3. Jane Juma
  4. Harran Mkocha
  5. John B Ochieng
  6. Gretchen M Cooley
  7. Richard Omore
  8. E Brook Goodhew
  9. Jamae F Morris
  10. Veronica Costantini
  11. Jan Vinjé
  12. Patrick J Lammie
  13. Jeffrey W Priest
  1. University of California, Berkeley, United States
  2. United States Centers for Disease Control and Prevention, United States
  3. Kenya Medical Research Institute, Kenya
  4. Kongwa Trachoma Project, United Republic of Tanzania
  5. Georgia State University, United States
  6. Task Force for Global Health, United States
Research Article
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Cite this article as: eLife 2019;8:e45594 doi: 10.7554/eLife.45594

Abstract

Little is known about enteropathogen seroepidemiology among children in low-resource settings. We measured serological IgG responses to eight enteropathogens (Giardia intestinalis, Cryptosporidium parvum, Entamoeba histolytica, Salmonella enterica, enterotoxigenic Escherichia coli, Vibrio cholerae, Campylobacter jejuni, norovirus) in cohorts from Haiti, Kenya, and Tanzania. We studied antibody dynamics and force of infection across pathogens and cohorts. Enteropathogens shared common seroepidemiologic features that enabled between-pathogen comparisons of transmission. Overall, exposure was intense: for most pathogens the window of primary infection was <3 years old; for highest transmission pathogens primary infection occurred within the first year. Longitudinal profiles demonstrated significant IgG boosting and waning above seropositivity cutoffs, underscoring the value of longitudinal designs to estimate force of infection. Seroprevalence and force of infection were rank-preserving across pathogens, illustrating the measures provide similar information about transmission heterogeneity. Our findings suggest antibody response can be used to measure population-level transmission of diverse enteropathogens in serologic surveillance.

Data availability

Analyses were conducted in R version 3.5.3. Data and computational notebooks used to complete the analyses are available through GitHub and the Open Science Framework (osf.io/r4av7).

The following data sets were generated

Article and author information

Author details

  1. Benjamin F Arnold

    Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, United States
    For correspondence
    benarnold@berkeley.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6105-7295
  2. Diana L Martin

    Division of Parasitic Diseases and Malaria, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jane Juma

    Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
    Competing interests
    The authors declare that no competing interests exist.
  4. Harran Mkocha

    Kongwa Trachoma Project, Kongwa, United Republic of Tanzania
    Competing interests
    The authors declare that no competing interests exist.
  5. John B Ochieng

    Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
    Competing interests
    The authors declare that no competing interests exist.
  6. Gretchen M Cooley

    Division of Parasitic Diseases and Malaria, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Richard Omore

    Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
    Competing interests
    The authors declare that no competing interests exist.
  8. E Brook Goodhew

    Division of Parasitic Diseases and Malaria, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Jamae F Morris

    Department of African-American Studies, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Veronica Costantini

    Division of Viral Diseases, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Jan Vinjé

    Division of Viral Diseases, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Patrick J Lammie

    Neglected Tropical Diseases Support Center, Task Force for Global Health, Decatur, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Jeffrey W Priest

    Division of Foodborne, Waterborne, and Environmental Diseases, United States Centers for Disease Control and Prevention, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (K01-AI119180)

  • Benjamin F Arnold

Bill and Melinda Gates Foundation (OPP1022543)

  • Patrick J Lammie

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: In Haiti, the human subjects protocol was reviewed and approved by the Ethical Committee of St. Croix Hospital (Leogane, Haiti) and the institutional review board at the US Centers for Disease Control and Prevention (CDC). After listening to an overview of the study, individuals were asked for verbal consent to participate. Verbal consent was deemed appropriate by both review boards because of low literacy rates in the study population. With each longitudinal visit, the study team re-consented participants before specimen collection. Mothers provided consent for children under 7, and children 7 years and older provided additional verbal assent. In Kenya, the human subjects protocol was reviewed and approved by institutional review boards at the Kenya Medical Research Institute (KEMRI) and at the US CDC. Primary caretakers provided written informed consent for their infant child's participation in the trial and blood specimen collection and testing. The original trial was registered at clinicaltrials.org (NCT01695304). In Tanzania, the human subjects protocol was reviewed and approved by the Institute for Medical Research Ethical Review Committee in Dar es Salaam, Tanzania and the institutional review board at the US CDC. Parents of enrolled children provided consent, and children 7 years and older also provided verbal assent before specimen collection.

Reviewing Editor

  1. Mark Jit, London School of Hygiene & Tropical Medicine, and Public Health England, United Kingdom

Publication history

  1. Received: January 29, 2019
  2. Accepted: August 15, 2019
  3. Accepted Manuscript published: August 19, 2019 (version 1)
  4. Version of Record published: September 16, 2019 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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Further reading

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    2. Medicine
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    Background:

    There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high dependency unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics.

    Methods:

    We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay.

    Results:

    Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors.

    Conclusions:

    Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly evolving situation.

    Funding:

    This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill & Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

    1. Epidemiology and Global Health
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    Research Article Updated

    Global targets to reduce salt intake have been proposed, but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based on simple predictors and applied this model to national surveys in 54 countries. We used 21 surveys with spot urine samples for the ML model derivation and validation; we developed a supervised ML regression model based on sex, age, weight, height, and systolic and diastolic blood pressure. We applied the ML model to 54 new surveys to quantify the mean salt consumption in the population. The pooled dataset in which we developed the ML model included 49,776 people. Overall, there were no substantial differences between the observed and ML-predicted mean salt intake (p<0.001). The pooled dataset where we applied the ML model included 166,677 people; the predicted mean salt consumption ranged from 6.8 g/day (95% CI: 6.8–6.8 g/day) in Eritrea to 10.0 g/day (95% CI: 9.9–10.0 g/day) in American Samoa. The countries with the highest predicted mean salt intake were in the Western Pacific. The lowest predicted intake was found in Africa. The country-specific predicted mean salt intake was within reasonable difference from the best available evidence. An ML model based on readily available predictors estimated daily salt consumption with good accuracy. This model could be used to predict mean salt consumption in the general population where urine samples are not available.