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Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification

Marcos Amaku1, Marcelo Nascimento Burattini1,2, Eleazar Chaib1

  • 1LIM01-Hospital de Clínicas, Faculdade de Medicina Universidade de São Paulo, São Paulo, SP, Brazil.

Theoretical Biology & Medical Modelling
|December 13, 2017
PubMed
Abstract

Insights

This study introduces a new method to estimate the true prevalence of infectious diseases, accounting for incomplete disease reporting. The model successfully estimated underreported hepatitis C cases in Brazil, highlighting its utility for public health surveillance.

Area of Science:

  • Epidemiology
  • Public Health
  • Mathematical Modeling

Background:

  • Disease notification systems are mandated by law but often suffer from incomplete reporting due to various factors.
  • The fraction of reported cases can vary significantly (9-99%), impacting accurate disease prevalence assessment.
  • Underreporting is a common challenge in tracking infectious diseases and other public health issues.

Purpose of the Study:

  • To propose a novel statistical method for estimating the full prevalence of infectious diseases, addressing incomplete notification.
  • To quantify the number of non-notified infections and improve the accuracy of disease transmission intensity parameters.
  • To demonstrate the method's applicability using the case of hepatitis C in Brazil.

Main Methods:

  • Developed a mathematical model that assumes incomplete incidence notification.
  • The model estimates the number of non-notified infections.
  • The method allows for iterative correction by comparing results with empirical data.

Main Results:

  • Applied to hepatitis C in Brazil, the model estimated a total infection prevalence between 1,597,540 and 1,616,153 cases.
  • Notified hepatitis C cases ranged from 163,902 to 169,382.
  • Non-notified hepatitis C cases were estimated between 1,433,638 and 1,446,771.

Conclusions:

  • The proposed model effectively estimates the true magnitude of endemic infectious diseases, especially when reported cases are only a fraction of the total.
  • This methodology can be valuable for public health surveillance and policy-making.
  • The approach has potential applications beyond infectious diseases, including underreported crime statistics.
Keywords:
Hepatitis CMathematical modelsNotifications system incidencePrevalence

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