Data Sources

1
Collaborative Course on Infectious
Diseases January 2009
LECTURE 3 Data Sources Data
Analysis Marcia C. Castro mcastro_at_hsph.harvard.e
du
Harvard School of Public Health Centro de
Pesquisa Gonçalo Moniz, Fundação Oswaldo Cruz
(Fiocruz) Brazil Studies Program, DRCLAS,
Harvard University
2
Objectives

• Describe the main data sources available for
  health-related research in Brazil
• Introduce basic demographic methods
• Describe spatial analytical approaches
• GIS, Remote Sensing, and Spatial Analysis

3
Questions for DiscussionData Sources

• What are the main data limitations for
  health-related analysis?
• What would be needed to fill in the gap(s)?
• How could available data be used for
  evidence-based planning of public health
  interventions?

4
Questions for DiscussionData Analysis

• How would a demographic analysis improve
  understanding of the 5 diseases focused in this
  course?
• How do the use of spatial tools in public health
  increase knowledge of disease dynamics?
• Is there a balance between local x global
  analysis?
• How can each approach inform policy makers?
• Which is most appropriate to evaluate the
  progress toward achieving the MDG?

5
Data Sources

• Three types of data
• Events
• Cases deaths
• Exposure (denominators)
• Population
• Clues on transmission mechanisms
• Multidisciplinary social, economic, demographic,
  behavior individual perception/knowledge,
  ecological, political, biological

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Data Sources

• What are we looking for?
• Time
• Space
• Population groups
• List of important sources available on the course
  website

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Data Sources Events

• Administrative data
• Outpatient / Hospitalization
• Reported cases
• Active / Passive
• Immunization
• Deaths
• Control activities
• Survey-based data

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Data Sources Denominators

• Population counts
• Census
• Every 10 years
• Civil register system
• Under enumeration
• Household surveys
• Sample
• Periodicity Coverage
• Projections
• Uncertainty

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Data Sources Multidisciplinary

• Census household surveys
• Agriculture
• Environment
• Land cover, land change, land use
• Climate
• Soil, hydrology
• Infrastructure
• Urban planning expansion
• Social programs (cash transfers)

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RIPSA - http//www.ripsa.org.br

• RIPSA Inter-agency Network of Information for
  Health (Rede Interagencial de Informações para a
  Saúde)
• Joint initiative of the Ministry of Health and
  the Pan-American Health Organization (PAHO)
• Annual publication of summary indicators
  (available on-line)

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RIPSA

• On-line database http//www.datasus.gov.br/idb

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Demographic Methods

• Population (P) numbers can only change by
• Births (B) Fertility
• Deaths (D) Mortality
• Movements in (I) / out (E) Migration
• Balancing equation
• Pt1 Pt Bt Dt It Et

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Demographic MethodsMortality

• Key indicators
• Infant mortality
• Child mortality
• Life expectancy at birth

1990
2005
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Demographic MethodsMortality

• Key tools
• Life tables
• Total deaths
• By cause of death
• Simulated scenarios of cause elimination
• Decompose differentials
• Inequalities
• Modeled mortality schedules
• Standards in the absence of good data
• Indirect methods of estimation

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Demographic MethodsFertility

• Key indicator Total Fertility Rate

PNDS 1996 and 2006
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Demographic MethodsFertility

• Key indicator
• Net Reproduction Rate
• Key tools
• Modeled fertility schedules
• Standards in the absence of good data
• Indirect methods of estimation

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Demographic MethodsMigration

• Migratory flow
• Direction
• Intensity
• Characteristics
• Interactive flow mapping

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Demographic MethodsAge and sex structure
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Demographic MethodsProjections
Births in the period

• Projecting denominators
• Use 3 population components
• Assumptions about future patterns
• Uncertainty

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Spatial Tools

• Visualization
• Exploration
• Modeling

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Framework for Spatial Data Analysis
Attribute data
Feature data
Databases
GIS Remote Sensing
Visualization
Maps
Describe significant patterns
Exploration
StatisticalSoftware
Test hypotheses
Modeling
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Visualization
Source Map 1. Published by C.F. Cheffins, Lith,
Southhampton Buildings, London, England, 1854 in
Snow, John. On the Mode of Communication of
Cholera, 2nd Ed, John Churchill, New Burlington
Street, London, England, 1855.
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Visualization Visceral Leishmaniasis, Pernambuco
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Visualization incidence ratesDengue Rio de
Janeiro
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Visualization prevalence rates
Schistosomiasis Mansoni Bahia
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Visualization prevalence rates
Schistosomiasis Mansoni Bahia
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Visualization variation in prevalence rates
Schistosomiasis Mansoni Bahia
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Patterns?

• Virgin Mary in a pancake

• Mermaid in clouds

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Exploration clustering
Machadinho Settlement Project, Rondônia State,
Brazilian Amazon
Significant clusters of low malaria rates No
significant clusters Significant clusters of high
malaria rates
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Modeling predictive model
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Modeling spatial diffusion
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Modeling diffusion
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Modeling diffusion
Schistosomiasis
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References

• Anselin, L. 2006. How (Not) to Lie with Spatial
  Statistics. American Journal of Preventive
  Medicine 30(2) S3-S6.
• Brownstein, J.S., C.A. Cassa, K.D. Mandl. 2006.
  No place to hide Re-identifying patients from
  published maps. New England Journal of Medicine
  355(16)1741-2.
• Kenneth Hill, Alan D Lopez, Kenji Shibuya,
  Prabhat Jha, on behalf of the Monitoring of Vital
  Events (MoVE) writing group. 2007. Interim
  measures for meeting needs for health sector
  data births, deaths, and causes of death. The
  Lancet 370(9600) 1726-1735.
• Werneck, GL et al. 2002. The urban spread of
  visceral leishmaniasis clues from spatial
  analysis. Epidemiology 13(3)364-367.

36
Questions for DiscussionData Sources

• What are the main data limitations for
  health-related analysis?
• What would be needed to fill in the gap(s)?
• How could available data be used for
  evidence-based planning of public health
  interventions?

37
Questions for DiscussionData Analysis

• How would a demographic analysis improve
  understanding of the 5 diseases focused in this
  course?
• How do the use of spatial tools in public health
  improve the understanding of disease dynamics?
• Is there a balance between local x global
  analysis?
• How can each approach inform policy makers?
• Which is most appropriate to evaluate the
  progress toward achieving the MDG?