DOI: 10.5061/dryad.rv15dv4gt
title: Data from: Present and future suitability of invasive and urban vectors through an environmentally-driven mosquito reproduction number

description: Temperature and water availability significantly influence mosquito
 population dynamics. We've devised a method, integrating experimental
 data with insights from mosquito and thermal biology, to calculate the
 basic reproduction number (RM) for urban mosquito species, Ae. albopictus
 and Ae. aegypti. RM represents the number of female mosquitoes produced by
 one female during her lifespan, indicating suitability for growth.
 Environmental conditions, including temperature, rainfall and human
 density influence RM by altering key mosquito life cycle traits.
 Validation using data from Spain and Europe confirms the approach's
 reliability. Our analysis suggests that temperature increases may not
 uniformly benefit Ae. albopictus proliferation but could boost Ae. aegypti
 expansion. We suggest using vector RM maps, leveraging climate and
 environmental data, to predict areas susceptible to invasive mosquito
 population growth. These maps aid in resource allocation for intervention
 strategies, supporting effective vector surveillance and management
 efforts.
description:  Presence-absence data spans the entire invasion process of
 <em>Ae. albopictus</em> in Spain from 2004 up to October 2023.
 Data from 2004 to 2014 originated from authoritative surveillance at the
 municipal level, mostly conducted through oviposition and adult traps.
 From 2014 to 2022, the data combined these authoritative methods with
 successful citizen science methodologies oriented towards surveillance
 (see daily updated maps in Europe at:
 https://map.mosquitoalert.com/spa/distribution/en). Spatially, the
 validation involved <em>Ae. albopictus</em> presence-absence
 presence data at the municipal level in five administrative regions of
 Spain (Andalusia, Aragon, Catalonia, Valencian Community, Basque Country).
 Also, at the European scale, we use presence-absence data for October 2023
 from the Mosquito Alert citizen science platform. It combines data from
 the ECDC agency and citizen science data. Presence-absence data at the
 European scale corresponds to administrative units at the NUTS 3 level,
 roughly matching the province level. Spanish municipalities, which are at
 a smaller scale than NUTS 3, provide presence-absence data at a finer
 resolution. Therefore we have two data sets with presence-absence, one for
 Europe and one for Spain with finer resolution. The mosquito trap count
 data originated from a total of 13 BG-Sentinel traps distributed across
 various municipalities in the NE Spain (Catalonia region) with the
 following numbers: Blanes (11), Lloret de Mar (1), Palafolls (1), Tordera
 (1). The traps operated from November 2020 until December 2022 for Blanes,
 from September 2020 until December 2022 for Palafolls, from May 2020 until
 December 2022 for Todera, from June 2020 until November 2020 for Lloret de
 Mar, and mosquito samples were collected every week.
 The code to reproduce all the figures in the manuscript is in a
 zip folder. 
description: # Present and future suitability of invasive and urban vectors through an
 environmentally-driven Mosquito Reproduction Number
 [https://doi.org/10.5061/dryad.rv15dv4gt](https://doi.org/10.5061/dryad.rv15dv4gt) ## Description of the data and file structure There are two data sets used in the validation of the suitability index. The BG trap female count data (BG_count_data_albopictus.csv) and the presence absence data (PA_Oct_2023_albopictus.csv) for *Aedes albopictus*. Presence-absence data spans the entire invasion process of *Aedes albopictus* in Spain from 2004 up to October 2023. Data from 2004 to 2014 originated from authoritative surveillance at the municipal level, mostly conducted through oviposition and adult traps. From 2014 to 2022, the data combined these authoritative methods with successful citizen science methodologies oriented towards surveillance (see daily updated maps in Europe at: \url{[https://map.mosquitoalert.com/spa/distribution/en}](https://map.mosquitoalert.com/spa/distribution/en})). Spatially, the validation involved \textit{Ae. albopictus} presence-absence presence data at the municipal level in five administrative regions of Spain (Andalusia, Aragon, Catalonia, Valencian Community, Basque Country). Also, at the European scale we use presence-absence data for October 2023 from the Mosquito Alert citizen science platform. It combines data from the ECDC agency and citizen science data. Presence-absence data at the European scale corresponds to administrative units at the NUTS 3 level, roughly matching the province level (albopictus_PA_EU.zip). Spanish municipalities, which are at a smaller scale than NUTS 3, provide presence-absence data at a finer resolution. Therefore we have two data sets with presence-absence, one for Europe and one for Spain with finer resolution. The mosquito trap count data originated from a total of 13 BG-Sentinel traps distributed across various municipalities in the NE Spain (Catalonia region) with the following numbers: Blanes (11), Lloret de Mar (1), Palafolls (1), Tordera (1). The traps operated from November 2020 until December 2022 for Blanes, from September 2020 until December 2022 for Palafolls, from May 2020 until December 2022 for Todera, from June 2020 until November 2020 for Lloret de Mar, and mosquito samples were collected every week. Structure of the data explanation of each column of the tabular data:  * BG_count*_*data_albopictus.csv * trap_name: name of the trap * province: spanish province where the trap is located * city: spanish city where the trap is located * start_date: date of placing the trap * end_date: date of recolection of the trap * trapping_effort: end_date-start_date * latitude: latitude of the trap's location * longitude: longitude of the trap's location * trap_type: type of the adult trap * females: number of females mosquitoes found in the trap during the start_date to end date_period * precipitation (mm): precipitation for the start_date * l7precipitation: accumulated precipiation during 7 days from the start_date * l14precipitation: accumulated precipiation during 14 days from the start_date * l21precipitation: accumulated precipiation during 21 days from the start_date * mean_temperature (degree C): mean temperature of the week from the start_date * population: number of inhabitants in the municipality where the trap is placed * PA_Oct_2023_albopictus:  * NATCODE: id of the municipality in Spain * MUNICIPIO_NOMBRE: name of the spanish municipality * PA: presence (1) absence (0) of *Aedes albopictus* in each municipality * albopictus_PA_EU.zip: zip containing shapefile with presence-absence *Aedes albopictus* in Europe * cntryName: country code in Europe * locCode: location code of the NUTS3 region in Europe * albopictus: state of the *Aedes albopictus *in each region. There are 7 posible cases: * absent: there is mosquito surveillance but the species has not been found in this region * noData: there is no mosquito surveillance in this region * PA: detected (1) - non detected (0) *Aedes albopictus* in this European region ## Sharing/Access information The data and code is also accesible in the Github repository: [https://github.com/mpardo1/RM_mosquito/](https://github.com/mpardo1/RM_mosquito/) ## Code/Software All the analysis was performed using R. The code to recreate the figures in the manuscript and supplementary material is in the zip folder RM_mosquito_code.zip. It is also avaliable in: [https://github.com/mpardo1/RM_mosquito/](https://github.com/mpardo1/RM_mosquito/) In the folder code there is one script for each of the figures in the main manuscript. The names of the code files and the figures in the main text are related as follows: * Figure 1: plot1.R * Figure 2 , Figure 4 and Figure 5: panel_camb_clim.R * Figure 3: panel_validation.R For the figures in the Supplementary material the respective code is in: * Figure S1: plot1.R * Figure S2: panel_thermal.R * Figure S3: panel_sensitivity.R * Figure S4-7: panel_camb_clim.R * Figure S8-9: panel_validation.R