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  1. 2. Data Assembly and Management
  2. 2.3 Routine Surveillance Data
  3. Contextual considerations
  • Code library for subnational tailoring
    English version
  • 1. Getting Started
    • 1.1 About and Contact Information
    • 1.2 For Everyone
    • 1.3 For the SNT Team
    • 1.4 For Analysts
    • 1.5 Producing High-Quality Outputs
  • 2. Data Assembly and Management
    • 2.1 Working with Shapefiles
      • Spatial data overview
      • Basic shapefile use and visualization
      • Shapefile management and customization
      • Merging shapefiles with tabular data
    • 2.2 Health Facilities Data
      • Fuzzy matching of names across datasets
      • Health facility coordinates and point data
    • 2.3 Routine Surveillance Data
      • Routine data extraction
      • DHIS2 data preprocessing
      • Determining active and inactive status
      • Contextual considerations
      • Missing data detection methods
      • Health facility reporting rate
      • Data coherency checks
      • Outlier detection methods
      • Imputation methods
      • Final database
    • 2.4 Stock Data
      • LMIS
    • 2.5 Population Data
      • National population data
      • WorldPop population raster
    • 2.6 National Household Survey Data
      • DHS data overview and preparation
      • Prevalence of malaria infection
      • All-cause child mortality
      • Treatment-seeking rates
      • ITN ownership, access, and usage
      • Wealth quintiles analysis
    • 2.7 Entomological Data
      • Entomological data
    • 2.8 Climate and Environmental Data
      • Climate and environment data extraction from raster
    • 2.9 Modeled Data
      • Generating spatial modeled estimates
      • Working with geospatial model estimates
      • Modeled estimates of malaria mortality and proxies
      • Modeled estimates of entomological indicators
  • 3. Stratification
    • 3.1 Epidemiological Stratification
      • Incidence overview and crude incidence
      • Incidence adjustment 1: incomplete testing
      • Incidence adjustment 2: incomplete reporting
      • Incidence adjustment 3: treatment-seeking
      • Incidence stratification
      • Prevalence and mortality stratification
      • Combined risk categorization
      • Risk categorization REMOVE?
      • Risk categorization REMOVE?
    • 3.2 Stratification of Determinants of Malaria Transmission
      • Seasonality
      • Access to Care
  • 4. Review of Past Interventions
    • 4.1 Case Management
    • 4.2 Routine Interventions
    • 4.3 Campaign Interventions
    • 4.4 Other Interventions
  • 5. Targeting of Interventions
  • 6. Retrospective Analysis
    • 6.1: Trend analysis
  • 7. Urban Microstratification

On this page

  • Overview
  • Background/Key Concepts
  • Step-by-step
  • Summary
  • Full Code
  1. 2. Data Assembly and Management
  2. 2.3 Routine Surveillance Data
  3. Contextual considerations

Contextual considerations

Overview

Overview

Objectives
  • Objective 1
  • Objective 2

Background/Key Concepts

Contextual considerations

- What types of facilities should be included in analysis?
- i.e. should labs that support larger facilities be counted separately
- ideally it is the larger facility that reports
- if not, is there potential double counting?
- lab consideration also raises questions about registers
- DHIS2 data comes from different registers (lab, ipd, opd, etc.)
- Helpful to note which register DHIS2 epidemiological elements come from
- Ideally each register reports the same confirmed cases, but in practice they may not
- Question of registers relates to facility type inclusions for laboratory facilities
- Here should we generally explore what the data looks like? types of facilities summaries, etc.

Step-by-step

Summary

Full Code

 

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