Climate Predicts Geographic and Temporal Variation in Mosquito-Borne Disease Dynamics on Two Continents

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show...

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Published inNature communications Vol. 12; no. 1; pp. 1233 - 13
Main Authors Caldwell, Jamie M, LaBeaud, A Desiree, Lambin, Eric F, Stewart-Ibarra, Anna M, Ndenga, Bryson A, Mutuku, Francis M, Krystosik, Amy R, Ayala, Efraín Beltrán, Anyamba, Assaf, Borbor-Cordova, Mercy J, Damoah, Richard, Grossi-Soyster, Elysse N, Heras, Froilán Heras, Ngugi, Harun N, Ryan, Sadie J, Shah, Melisa M, Sippy, Rachel, Mordecai, Erin A
Format Journal Article
LanguageEnglish
Published Goddard Space Flight Center Nature Research 23.02.2021
Nature Publishing Group UK
Nature Publishing Group
Nature Portfolio
Subjects
631/158
631/158/1144
631/158/1469
631/158/2165
692/699/255
Aedes aegypti
Animals
Basic Reproduction Number
Calibration
Children
Climate Change
Climate effects
Climate models
Climate prediction
Context
Culicidae - physiology
Dengue fever
Disease
Disease Outbreaks
Dynamics
Ecuador - epidemiology
Epidemics
Geography
Humanities and Social Sciences
Humans
Infectious diseases
Kenya - epidemiology
Laboratories
Life Sciences (General)
Meteorology and Climatology
Models, Biological
Mosquitoes
multidisciplinary
Natural populations
Nonlinear Dynamics
Outbreaks
Population dynamics
Science
Science (multidisciplinary)
Socioeconomic Factors
Spatio-Temporal Analysis
Temporal variations
Time Factors
Vector Borne Diseases - epidemiology
Vector Borne Diseases - transmission
Vector-borne diseases
Vectors
Viruses
Kenya
Ecuador
Infectious Diseases
Ecological Modelling
Ecology
Climate-Change Ecology
Ecological Epidemiology
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Abstract Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88%for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
AbstractList Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of the mosquito Aedes aegypti into climate-driven mechanistic models to predict number, timing, and duration of outbreaks in Ecuador and Kenya.
The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of the mosquito Aedes aegypti into climate-driven mechanistic models to predict number, timing, and duration of outbreaks in Ecuador and Kenya.
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections. The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of the mosquito Aedes aegypti into climate-driven mechanistic models to predict number, timing, and duration of outbreaks in Ecuador and Kenya.
ArticleNumber 1233
Audience PUBLIC
Author Shah, Melisa M
LaBeaud, A Desiree
Ayala, Efraín Beltrán
Damoah, Richard
Ngugi, Harun N
Anyamba, Assaf
Heras, Froilán Heras
Ndenga, Bryson A
Stewart-Ibarra, Anna M
Mordecai, Erin A
Grossi-Soyster, Elysse N
Lambin, Eric F
Mutuku, Francis M
Caldwell, Jamie M
Krystosik, Amy R
Sippy, Rachel
Borbor-Cordova, Mercy J
Ryan, Sadie J
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/33623008$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords Infectious Diseases
Ecological Modelling
Ecology
Climate-Change Ecology
Ecological Epidemiology
Language English
License Creative Commons License: CCBY
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Notes GSFC
Goddard Space Flight Center
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SSID ssj0000391844
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Snippet Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For...
The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of...
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StartPage 1233
SubjectTerms 631/158
631/158/1144
631/158/1469
631/158/2165
692/699/255
Aedes aegypti
Animals
Basic Reproduction Number
Calibration
Children
Climate Change
Climate effects
Climate models
Climate prediction
Context
Culicidae - physiology
Dengue fever
Disease
Disease Outbreaks
Dynamics
Ecuador - epidemiology
Epidemics
Geography
Humanities and Social Sciences
Humans
Infectious diseases
Kenya - epidemiology
Laboratories
Life Sciences (General)
Meteorology and Climatology
Models, Biological
Mosquitoes
multidisciplinary
Natural populations
Nonlinear Dynamics
Outbreaks
Population dynamics
Science
Science (multidisciplinary)
Socioeconomic Factors
Spatio-Temporal Analysis
Temporal variations
Time Factors
Vector Borne Diseases - epidemiology
Vector Borne Diseases - transmission
Vector-borne diseases
Vectors
Viruses
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Title Climate Predicts Geographic and Temporal Variation in Mosquito-Borne Disease Dynamics on Two Continents
URI https://ntrs.nasa.gov/citations/20210011346
https://link.springer.com/article/10.1038/s41467-021-21496-7
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Volume 12
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