TY - JOUR

T1 - A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations

AU - Whittaker, Charles

AU - Winskill, Peter

AU - Sinka, Marianne

AU - Pironon, Samuel

AU - Massey, Claire

AU - Weiss, Daniel J

AU - Nguyen, Michele

AU - Gething, Peter W

AU - Kumar, Ashwani

AU - Ghani, Azra

AU - Bhatt, Samir

PY - 2022

Y1 - 2022

N2 - Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four 'dynamical archetypes', each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.

AB - Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four 'dynamical archetypes', each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.

KW - Animals

KW - Anopheles

KW - Climate

KW - Mosquito Control/methods

KW - Mosquito Vectors

KW - Population Dynamics

KW - Seasons

U2 - 10.1098/rspb.2022.0089

DO - 10.1098/rspb.2022.0089

M3 - Journal article

C2 - 35414241

VL - 289

JO - Proceedings of the Royal Society B: Biological Sciences

JF - Proceedings of the Royal Society B: Biological Sciences

SN - 0962-8452

IS - 1972

M1 - 20220089

ER -