ブラジルの連邦区における疫学的な監視のためのジオコード技術の使用:デング熱を用いた事例研究
Lucas Sanglard1, Klauss K S Garcia2, Walter Massa Ramalho3
1Ministry of Health, Secretariat of Health Surveillance and Environment, Brasília.
Geospatial health
|September 2, 2025
まとめ
デング熱の監視のためのジオコーディングサービスを比較すると,Google Maps APIとCNEFEが最高の精度を示しました. これらのツールは,流行病学的監視における介入の優先順位を特定するのに価値があります.
科学分野:
- 流行病学について
- 地理情報システム (GIS)
- 公衆衛生
背景:
- 疫学的な監視と資源の配分には正確なジオコーディングが不可欠です.
- デング熱の監視は 適切なタイミングで介入するための正確な位置データに依存しています
- 公共衛生戦略の最適化には ジオコードサービスの評価が不可欠です
研究 の 目的:
- 疫学的監視のための異なるジオコードサービスの正確性と適用性を比較する.
- デング熱症例データを用いて,Google Maps,CNEFE,OpenStreetMap (OSM),ArcGISなどのジオコーディングツールを評価する.
- 公衆衛生における核密度分析のための最も効果的なジオコーディング方法を決定する.
主な方法:
- ブラジルのSINANデータベースからのデング熱症例報告を用いた横断的記述研究 (2014).
- CNEFEからの完全な郵便番号 (CEP) データを黄金基準として使用して評価された地理コード精度.
- 4つのジオコーディングツール (Google Maps API,CNEFE,OSM,ArcGIS) は,精度と平均空間誤差 (MSE) に基づいて評価されました.
主要な成果:
- Google Maps APIは17.6%の精度 (MSE: 178.89km),CNEFEは9.0% (MSE: 17.24km),OSMは7.1% (MSE: 564.19km),そしてArcGISは3.7% (MSE: 2001.33km) を達成した.
- Google Maps APIとCNEFEは,全体的な精度が低いにもかかわらず,カーネルの密度分析において有効性を示した.
- 上位2つのモデルを用いた核密度分析は,デング熱症例の類似した空間パターンを明らかにした.
結論:
- Google Maps APIは,流行病学的監視における地理的参照に推奨され,その後はCNEFEが推奨されます.
- ジオコードサービスの選択は,精度と利用可能な資金の両方を考慮する必要があります.
- 効果的なジオコーディングは,公衆衛生介入の優先事項を特定するために不可欠です.
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