感染症のダイナミクスをモデル化して,世界保健の複雑な状況の中で,感染症のダイナミクスをモデル化する

Hans Heesterbeek¹, Roy M Anderson², Viggo Andreasen³

¹Faculty of Veterinary Medicine, University of Utrecht, Utrecht, Netherlands. j.a.p.heesterbeek@uu.nl.

Science (New York, N.Y.)

|March 14, 2015

まとめ

伝染性の病原体は,スケールを超えて複雑なダイナミクスを持つ健康を脅かす. 数学的モデルは,感染パターンを理解し,世界的な健康に関する意思決定を伝える上で極めて重要です.

科学分野:

エピデミオロジーエピデミオロジー
数学生物学数学生物学について
エコロジーエコロジーエコロジー

背景:

感染症は,制御の努力にもかかわらず,世界的な健康への重大な脅威であり続けています.
病原体ダイナミクスには,複数のスケールで複雑な生態学的および進化的プロセスが含まれます.
抗菌剤耐性や人間の接続性の向上などの要因は,病気の蔓延を悪化させる.

研究の目的:

感染症の拡散の多面性を強調する.
病原菌の理解と制御における数学モデリングの重要性を強調する.
世界保健の意思決定における定量的な証拠の必要性を強調する.

主な方法:

感染症の生態学的および進化的動態のレビュー.
病原体の感染経路 (直接的,間接的,ベクトル媒介,環境) の分析.
病気の蔓延に影響を及ぼす要因の議論と疾病管理の課題.

主要な成果:

感染症のダイナミクスは,様々な時間,組織,空間的なスケールで作用します.
病原体の伝播は,単一のまたは複数の宿主,ベクター,環境貯水池を含む,幅広く変化します.
数学的モデルは,複雑な疫学データを合成するための不可欠な枠組みを提供します.

結論:

数学的モデリングは,複雑な疫学的パターンを理解するために不可欠です.
モデルから得られた定量的なエビデンスは,効果的な世界的な健康戦略をサポートします.
感染症の脅威に対処するには,生態学的,進化的,社会的要因を考慮した統合的なアプローチが必要です.

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