DOI: 10.5061/dryad.1g1jwsv9w
title: Ecological and socioeconomic factors associated with reported tick-borne viruses

description: Background: Public health resources are often allocated based on reported
 disease cases. However, for under-recognized infectious diseases such as
 tick-borne viruses, risk assessments should also account for ecological
 and socioeconomic factors that influence disease case reporting. This
 study identifies country-level predictors of tick-borne virus reporting
 and evaluates whether wealthier nations are more likely to report
 resource-intensive cases. Methods: We applied boosted regression trees, a
 robust machine learning algorithm, to a comprehensive global database of
 tick-borne viruses and 24 environmental and socioeconomic variables.
 Results: Countries with lower income inequality and greater expertise in
 veterinary, agricultural, or forestry sectors are more likely to report
 tick-borne virus cases. Wealthier nations with stronger institutional and
 professional capacity exhibit higher reporting rates, whereas countries
 affected by conflict or limited health infrastructure show underreporting.
 Climatic factors, particularly subarctic environments, also contribute to
 reporting likelihood, complementing the effects of socioeconomic drivers.
 Conclusions: Disease reporting is shaped by both ecological context and
 socioeconomic capacity. Strengthening surveillance through targeted
 resource allocation and better integration of veterinary and public health
 expertise under the One Health framework could enhance global tick-borne
 disease mitigation. These findings provide valuable evidence to support
 the World Health Organization’s Global Arbovirus Initiative and emphasize
 the need for equitable disease surveillance across regions.
description: # Ecological and socioeconomic factors associated with reported tick-borne
 viruses Dataset DOI:
 [10.5061/dryad.1g1jwsv9w](https://doi.org/10.5061/dryad.1g1jwsv9w) ##
 Description of the data and file structure ### Files and variables ####
 File: 1_DataCleaning_TraitMatrix_v2.Rmd **Description:** Script for data
 processing to create global trait matrix. The final file output
 (global_trait_matrix_20251031.csv) will be merged with ZOVER outcome data.
 This data cleaning script is only helpful for those who want to see what
 steps I used to go from raw to clean covariates. Because underlying data
 are not CC0 compatible, we have removed the raw data but direct users to
 Data Availability below or **Supplementary table 5** to find the raw data
 to plug into the data cleaning script.  #### File:
 2_DataCleaning_ZOVER_v2.Rmd **Description:** Script for data processing to
 create tick-virus outcomes. The final file output
 (zover_toprecognized_complete_pubmed_20240921.csv) will be used as the
 model outcomes. This data cleaning script is only helpful for those who
 want to see what steps I used to go from raw to clean tick-virus data
 using ZOVER data. Because underlying data are not CC0 compatible, we have
 removed the raw data but direct users to Data Availability below
 or **Supplementary table 5** to find the raw data to plug into the data
 cleaning script.  ## File: zover_toprecognized_slim_pubmed_20251103.csv
 **Description:** Cleaned data for tick-virus outcomes. This dataset will
 be merged with cleaned covariate data for boosted regression analysis.
 **Variables:**  * **admin**: country name provided by
 `rnaturalearth` package * **iso_a3**: country code provided
 by `rnaturalearth` package  * **tbv_presence**:  binary code for a country
 based on having a reported tick-borne virus (1 = present, 0 = absent).
 Tick-borne virus data comes from ZOVER database. * **tbv_total**: numeric
 value for a country based on the total number of reported tick-borne
 viruses. Tick-borne virus data comes from ZOVER database. *
 **pubmedcitation_percounty_total**: numeric value for total PubMed
 citations regarding select tick-borne viruses. Citations were generated
 from the `easyPubMed` package and aggregated for each country.  #### File:
 global_trait_matrix_20251031.csv **Description:** Cleaned data for global
 trait matrix. This dataset will be merged with cleaned tick-virus data for
 boosted regression analysis. **Variables:** * **admin**: country name
 provided by `rnaturalearth` package * **iso_a3**: country code provided
 by `rnaturalearth` package * **country**:  country name provided
 by `rnaturalearth` package * **wb_forested_pct**: percent of country that
 is considered forested from World Bank (WB). See Data Availability below
 (or Supplementary table 5) for more source information. *
 **wb_landarea_sqkm**: total land area (sq km) of a country from World Bank
 (WB). See Data Availability below (or Supplementary table 5) for more
 source information. * **wb_livestockprod_index**: livestock production
 index from World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_accesselect_pct**: percentage
 of the population that has access to electricity from the World Bank (WB).
 See Data Availability below (or Supplementary table 5) for more source
 information. * **wb_expendedu_pct**: percentage of education spending
 based on country's GNI  from the World Bank (WB). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **wb_adultlit_rate**: rate of adult literacy (adults over 15)  from the
 World Bank (WB). See Data Availability below (or Supplementary table 5)
 for more source information. * **wb_gradvetsforestag_pct**: percent of
 tertiary graduates from veterinary, forestry, or agricultural programs
 from the World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_gradhealthwelf_pct**: percent
 of tertiary graduates from healthcare or welfare programs from the World
 Bank (WB). See Data Availability below (or Supplementary table 5) for more
 source information. * **wb_expendhealth_pct**: percent of healthcare
 spending based on country’s GDP from the World Bank (WB). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **wb_gini_index**: gini index (as a relative measure of inequality) 
 from the World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_povertyline_pct**: percent of
 population living below national poverty line from the World Bank (WB).
 See Data Availability below (or Supplementary table 5) for more source
 information. * **wb_employedag**: percent of population employed in
 agriculture from the World Bank (WB). See Data Availability below (or
 Supplementary table 5) for more source information. * **wb_urbanpop_pct**:
 percent of population living in urban areas from the World Bank (WB). See
 Data Availability below (or Supplementary table 5) for more source
 information. * **wb_pestimportstot_mean**: average pesticide imports based
 on USD$ from the World Bank (WB). See Data Availability below (or
 Supplementary table 5) for more source information. *
 **who_reportntd_mean**: annual average reported number of people being
 treated for neglected tropical diseases (NTDs) from the World Health
 Organization’s Global Health Observation database. See Data Availability
 below (or Supplementary table 5) for more source information. *
 **sedac_popcounts_sum**: human population counts from gridded population
 from NASA’s SEDAC database. See Data Availability below (or Supplementary
 table 5) for more source information. * **grdi_shdi_mean**: average social
 vulnerability index from GRDI (0 to 1, least vulnerable to most
 vulnerable). See Data Availability below (or Supplementary table 5) for
 more source information. * **glw_livestockdensity_mean**: average
 livestock density from gridded cattle dataset (GLW v4). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **ee_vegdisim_mean**: average vegetation dissimilarity index from
 EarthEnv (higher values represent more habitat fragmented locations). See
 Data Availability below (or Supplementary table 5) for more source
 information. * **wwf_ecoreg_total**: total ecoregions per country from
 World Wildlife Fund (WWF) Olson et al. 2004. See Data Availability below
 (or Supplementary table 5) for more source information. *
 **humanpop_count**:  human population counts from gridded population from
 NASA’s SEDAC database. See Data Availability below (or Supplementary table
 5) for more source information. * **sdhi_mean**: average social
 vulnerability index from GRDI (0 to 1, least vulnerable to most
 vulnerable). See Data Availability below (or Supplementary table 5) for
 more source information. * **livestock_mean**: average livestock density
 from gridded cattle dataset (GLW v4). See Data Availability below (or
 Supplementary table 5) for more source information. * **vegdisim_mean**:
 average vegetation dissimilarity index from EarthEnv (higher values
 represent more habitat fragmented locations). See Data Availability below
 (or Supplementary table 5) for more source information. *
 **ivsa_chapter**: binary code for the presence/absence (1/0) of an
 International Veterinary Student’s Association chapter.  See Data
 Availability below (or Supplementary table 5) for more source information.
 * **fao_pestusecapita_kmp**: pesticide use per capita (kilometer per
 person) from the Food and Agriculture Organization (FAO). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **kopp_climatezone_ID**: Köppen-Geiger climate classiciation zone ID
 based on Rubel and Kottek 2010. See Data Availability below (or
 Supplementary table 5) for more source information. *
 **kopp_climatezone_name**: Köppen-Geiger climate classiciation zone name
 based on Rubel and Kottek 2010. See Data Availability below (or
 Supplementary table 5) for more source information. *
 **acled_conflictexposure_pct**: percentage of the total population exposed
 to conflict within 5 km based on Raleigh et al. 2023. See Data
 Availability below (or Supplementary table 5) for more source information.
 * **acled_conflictexposure_total**: total number of conflict events per
 country based on Raleigh et al. 2023. See Data Availability below (or
 Supplementary table 5) for more source information. #### File:
 zover_matrix_formatted_preBRT_20251103.csv **Description:** Cleaned and
 formatted dataset for boosted regression tree analysis. This data will
 also be used for figures and tables.  **Variables:** * **admin**: country
 name provided by `rnaturalearth` package * **iso_a3**: country code
 provided by `rnaturalearth` package * **tbv_presence**:  binary code for a
 country based on having a reported tick-borne virus (1 = present, 0 =
 absent). Tick-borne virus data comes from ZOVER database. * **tbv_total**:
 numeric value for a country based on the total number of reported
 tick-borne viruses. Tick-borne virus data comes from ZOVER database. *
 **country**:  country name provided by `rnaturalearth` package *
 **wb_forested_pct**: percent of country that is considered forested from
 World Bank (WB). See Data Availability below (or Supplementary table 5)
 for more source information. * **log_wb_landarea_sqkm**: log10-transformed
 total land area (sq km) of a country from World Bank (WB). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **log_wb_livestockprod_index**: log10-transformed livestock production
 index from World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_accesselect_pct**: percentage
 of the population that has access to electricity from the World Bank (WB).
 See Data Availability below (or Supplementary table 5) for more source
 information. * **wb_expendedu_pct**: percentage of education spending
 based on country's GNI  from the World Bank (WB). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **wb_adultlit_rate**: rate of adult literacy (adults over 15)  from the
 World Bank (WB). See Data Availability below (or Supplementary table 5)
 for more source information. * **wb_gradvetsforestag_pct**: percent of
 tertiary graduates from veterinary, forestry, or agricultural programs
 from the World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_gradhealthwelf_pct**: percent
 of tertiary graduates from healthcare or welfare programs from the World
 Bank (WB). See Data Availability below (or Supplementary table 5) for more
 source information. * **wb_expendhealth_pct**: percent of healthcare
 spending based on country’s GDP from the World Bank (WB). See Data
 Availability below (or Supplementary table 5) for more source information.
 * **wb_gini_index**: gini index (as a relative measure of inequality) 
 from the World Bank (WB). See Data Availability below (or Supplementary
 table 5) for more source information. * **wb_povertyline_pct**: percent of
 population living below national poverty line from the World Bank (WB).
 See Data Availability below (or Supplementary table 5) for more source
 information. * **wb_employedag**: percent of population employed in
 agriculture from the World Bank (WB). See Data Availability below (or
 Supplementary table 5) for more source information. * **wb_urbanpop_pct**:
 percent of population living in urban areas from the World Bank (WB). See
 Data Availability below (or Supplementary table 5) for more source
 information. * **log_who_reportntd_mean**: log10-transformed annual
 average reported number of people being treated for neglected tropical
 diseases (NTDs) from the World Health Organization’s Global Health
 Observation database. See Data Availability below (or Supplementary table
 5) for more source information. * **log_sedac_popcounts_sum**:
 log10-transformed human population counts from gridded population from
 NASA’s SEDAC database. See Data Availability below (or Supplementary table
 5) for more source information. * **grdi_shdi_mean**: average social
 vulnerability index from GRDI (0 to 1, least vulnerable to most
 vulnerable). See Data Availability below (or Supplementary table 5) for
 more source information. * **ee_vegdisim_mean**: average vegetation
 dissimilarity index from EarthEnv (higher values represent more habitat
 fragmented locations). See Data Availability below (or Supplementary table
 5) for more source information.  * **wwf_ecoreg_total**: total ecoregions
 per country from World Wildlife Fund (WWF) Olson et al. 2004. See Data
 Availability below (or Supplementary table 5) for more source information.
 * **ivsa_chapter**: binary code for the presence/absence (1/0) of an
 International Veterinary Student’s Association chapter.  See Data
 Availability below (or Supplementary table 5) for more source
 information.  * **kopp_climatezone_name**: Köppen-Geiger climate
 classiciation zone name based on Rubel and Kottek 2010. See Data
 Availability below (or Supplementary table 5) for more source
 information.  * **acled_conflictexposure_pct**: percentage of the total
 population exposed to conflict within 5 km based on Raleigh et al.
 2023. See Data Availability below (or Supplementary table 5) for more
 source information.  * **log_acled_conflictexposure_total**:
 log10-transformed total number of conflict events per country based on
 Raleigh et al. 2023. See Data Availability below (or Supplementary table
 5) for more source information. * **log_pubmedcitation_percounty_total**:
 log10-transformed numeric value for total PubMed citations regarding
 select tick-borne viruses. Citations were generated from the
 `easyPubMed` package and aggregated for each country.  *
 **log_fao_pestusecapita_kmp**: log10-transformed pesticide use per capita
 (kilometer per person) from the Food and Agriculture Organization
 (FAO). See Data Availability below (or Supplementary table 5) for more
 source information. * **log_glw_livestockdensity_mean**: log10-transformed
 average livestock density from gridded cattle dataset (GLW v4). See Data
 Availability below (or Supplementary table 5) for more source information.
 #### File: 3_Analysis_BRT_v2.Rmd **Description:** Script for running
 boosted regression trees for the (1) TBV presence model and (2) PubMed
 citation model. The final file outputs (1)
 brt_result_presence_20251103.rds and (2) brt_result_citation_20251103.rds
 are used for figures and tables in the manuscript. #### File:
 brt_result_presence_20251103.rds **Description:** Results from the boosted
 tree analysis for the tick-borne presence model. These results are used
 for figures and tables in the manuscript.  #### File:
 brt_result_citation_20251103.rds **Description:** Results from the boosted
 tree analysis for the PubMed citation model. These results are used for
 figures and tables in the manuscript.  #### File: vinf_data_20251103.txt
 **Description:** Results from the final TBV presence boosted regression
 tree model. These results reflect the variable importance of each
 covariate from our model and are used for figures and tables in the
 manuscript. **Variables:** * **var**: variable name * **rel.inf**: mean
 relative influence of individual variable within boosted regression tree
 model (%) * **rse**: standard error of relative influence of individual
 variable within boosted regression tree model (%) * **rvar**: mean
 variable of relative influence of individual variable within boosted
 regression tree model (%) * **response_rank**: rank of variables from most
 influential (1) to least influential (24) #### File:
 hsearch_paramtuning_datasummary_20251103.csv **Description:** Results from
 the hyperparameter tuning for the TBV presence boosted regression tree
 model. These are the results from the training runs and are used in
 supplementary figures.  **Variables:** * row: row ID of result from
 hyperparamter tuning grid search * trainAUC: training AUC from presence
 boosted regression tree model resulting from hyperparamter tuning grid
 search * testAUC: test AUC from presence boosted regression tree
 model resulting from hyperparamter tuning grid search * sen: sensitivity
 of presence boosted regression tree model resulting from hyperparamter
 tuning grid search * spec: specificity of presence boosted regression tree
 model resulting from hyperparamter tuning grid search * best: model metric
 from presence boosted regression tree model resulting from hyperparamter
 tuning grid search * n.trees: number of trees parameter from presence
 boosted regression tree model resulting from hyperparamter tuning grid
 search * interaction.depth: interaction depth of trees from presence
 boosted regression tree model resulting from hyperparamter tuning grid
 search * shrinkage: shrinkage (learning rate) from presence boosted
 regression tree model resulting from hyperparamter tuning grid search *
 n.minobsinnode: number of minimum observation per tree node from presence
 boosted regression tree model resulting from hyperparamter tuning grid
 search * seed: random seed from presence boosted regression tree
 model resulting from hyperparamter tuning grid search * id: ID of
 individual result from presence boosted regression tree model resulting
 from hyperparamter tuning grid search * id2: ID of individual result
 from presence boosted regression tree model resulting from hyperparamter
 tuning grid search #### File: 4_Results_SummariesTables.Rmd
 **Description:** Script to run result summaries within text and tables in
 the manuscript. #### File: 5_Figures_v2.Rmd **Description:** Script to
 recreate figures in the main and supplementary text. #### File:
 zover_toprecognized_complete_pubmed \_20240921.csv **Description:** Data
 to run summaries on the full pubmed dataset. Only helpful for some
 supplemental figures. **Variables:**  * **admin**: country name provided
 by `rnaturalearth` package * **iso_a3**: country code provided
 by `rnaturalearth` package  * **tbv_presence**:  binary code for a country
 based on having a reported tick-borne virus (1 = present, 0 = absent).
 Tick-borne virus data comes from ZOVER database. * **tbv_total**: numeric
 value for a country based on the total number of reported tick-borne
 viruses. Tick-borne virus data comes from ZOVER database. *
 **fix_viruses**: name of tick-borne virus that was standardized after
 pulling data down from ZOVER database. * **viral_family**: name of the
 family for reported tick-borne virus. Tick-borne virus data comes from
 ZOVER database. * **type**: type of virus (e.g., double strand RNA, single
 strand DNA). Tick-borne virus data comes from ZOVER database. *
 **continent**: location of where tick-borne virus sample originated
 from. Tick-borne virus data comes from ZOVER database. * **year_agg**:
 assigned year of when tick-borne virus sample was collected, years were
 aggregated every five years. Tick-borne virus data comes from ZOVER
 database. * **from_tick**: name of tick species of where the tick-borne
 virus sample was collected from. Tick-borne virus data comes from ZOVER
 database. * **tick_genus**: name of tick genus of where the tick-borne
 virus sample was collected from. Tick-borne virus data comes from ZOVER
 database. * **references**: source of where tick-borne virus record
 originated from.  Tick-borne virus data comes from ZOVER database. *
 **sample_type**: type of sample (e.g., tick, culture) of where tick-borne
 virus record originated from.  Tick-borne virus data comes from ZOVER
 database. * **viruses**: raw tick-borne virus name from ZOVER database. *
 **iso3c**: country code from `rnaturalearth` package *
 **pubmedcitation_percounty_total**: numeric value for total PubMed
 citations regarding select tick-borne viruses. Citations were generated
 from the `easyPubMed` package and aggregated for each country.  #### File:
 Manuscript_ZOVERTBVs_DataAvailability_20251031.pdf **Description:** Data
 availability statement as seen in Supplementary table 5. ## Code/software
 software: R version 4.4.1 (2024-06-14) packages: * countrycode_1.6.1 *
 easyPubMed_2.13 * gbm_2.2.2 * ggplot2_4.0.0 * ggpubr_0.6.0 *
 InformationValue_1.3.1 * janitor_2.2.0 * lubridate_1.9.3 * naniar_1.1.0 *
 openxlsx_4.2.7.1 * patchwork_1.3.0 * plotrix_3.8-4 * readr_2.1.5 *
 RColorBrewer_1.1-3 * rgho_3.0.2 * rnaturalearth_1.0.1 * ROCR_1.0-11 *
 rsample_1.2.1 * rworldmap_1.3-8 * scales_1.4.0 * sf_1.0-21 * stringr_1.5.2
 * terra_1.8-70 * tidyverse_2.0.0 * wbstats_1.0.4 ## Access information
 **DATA AVAILABILITY** This table summarizes metadata for all variables
 used in the analysis. “Variable ID” corresponds to the term used in the
 manuscript figures. “Variable details” provide additional information to
 locate each indicator and its associated data source. The “Temporal scale”
 column describes the reference period or time range covered by each
 dataset. Many indicators were obtained from the World Bank (WB) using the
 `wbstats` R package (Piburn 2020
 [https://doi.org/10.11578/dc.20171025.1827](https://doi.org/10.11578/dc.20171025.1827)). Data from the World Health Organization (WHO) were accessed via the `rgho` R package Filipovic-Pierucci 2024 [https://CRAN.R-project.org/package=rgho](https://cran.r-project.org/package=rgho)). Full source attributions are listed below the table and can be found in manuscript **Supplementary table 5.** | Source | Variable ID | Variable details | Temporal scale | | :----- | :---------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------ | | 1 | Forested | Forest area (% of land area) (WB: AG.LND.FRST.ZS) |  The average value of reported values between 2015-2023 | | 2 | Livestock Production | Livestock production index (2014-2016 = 100) (WB: AG.PRD.LVSK.XD) | The average value of reported values between 2010-2023 | | 3 | Pesticides | Pesticides use per capita (WB: FAO\_RP\_5172) | The average value of reported values between 2015-2023 | | 4 | Vet/Ag/Forest Grads | Percentage of graduates from tertiary education graduating from Agriculture, Forestry, Fisheries and Veterinary programmes, both sexes (%) (WB: SE.TER.GRAD.AG.ZS) | The average value of reported values between 2015-2023 | | 5 | Health/Welfare Grads | Percentage of graduates from tertiary education graduating from Health and Welfare programmes, both sexes (%) (WB: SE.TER.GRAD.HL.ZS) | The average value of reported values between 2015-2023 | | 6 | Adult Literacy | Literacy rate, adult total (% of people ages 15 and above) (WB: SE.ADT.LITR.ZS) | The average value of reported values between 2015-2023 | | 7 | Education Expenditure | Adjusted savings: education expenditure (% of GNI) (WB: NY.ADJ.AEDU.GN.ZS) | The average value of reported values between 2015-2023 | | 8 | Healthcare Expenditure | Current health expenditure (% of GDP) (WB: SH.XPD.CHEX.GD.ZS) | The average value of reported values between 2015-2023 | | 9 | Gini Index | Gini index (WB: SI.POV.GINI) | The average value of reported values between 2015-2023 | | 10 | Below Poverty Line | Poverty headcount ratio at national poverty lines (% of population) (WB: SI.POV.NAHC) | The average value of reported values between 2015-2023 | | 11 | Electricity Access | Access to electricity (% of population) (WB: EG.EL.ACCS.ZS) | The average value of reported values between 2015-2023 | | 12 | Land Area | Land area (sq. km) (WB: AG.LND.TOTL.K2) | The average value of reported values between 2015-2023 | | 13 | Urban Population | Urban population (% of total population) (WB: SP.URB.TOTL.IN.ZS) | The average value of reported values between 2015-2023 | | 14 | Employed in Agriculture | Employment in agriculture (% of total employment) (modeled ILO estimate) (WB: SL.AGR.EMPLY.ZS) | The average value of reported values between 2015-2023 | | 15 | NTD Treatment | Average annual number of people requiring mass treatment for at least one Neglected Tropical Disease (NTD) (WHO: SDGNTDTREATMENT) | The average value of reported values between 2010-2023 | | 16 | Population Counts | SEDAC CIEN Gridded Population of the World (GPW), v4 (\~5 km) | 2015 | | 17 | Social Vulnerability | SEDAC CIEN Subnational Human Development Index (SHDI) from the Global Gridded  Relative Deprivation Index (GRDI) (\~20 km) | The average value between 2010-2020 | | 18 | Livestock density | Gilbert et al. 2022. Livestock density (\~1 km) | 2015 | | 19 | Habitat Fragmentation | Tuanmu et al. 2015 Vegetation Dissimilarity (\~5 km) | 2005 | | 20 | Total Ecoregions | Olson et al. 2004 Ecoregions | 1995 | | 21 | Köppen-Geiger Climate Zone | Rubel and Kottek 2010 Koppen-Gieger climate classification zone | Represents the conditions between 1986-2010 | | 22 | Conflict exposure (total events) | ACLED Total conflicts | 2020-2023 | | 23 | Conflict exposure (% of population) | ACLED Percentage of population exposed to conflicts | 2020-2023 | | 24 | IVSA Chapter Present | IVSA Presence of an International Veterinary Student’s Association chapter | Presence as of 2023 | **^1^World Bank.** “Forest area (% of land area)” *World Development Indicators*, Food and Agriculture Organization of the United States (FAO), [https://data.worldbank.org/indicator/AG.LND.FRST.ZS](https://data.worldbank.org/indicator/AG.LND.FRST.ZS). Accessed 31 Oct. 2025. **^2^World Bank.** “Livestock production index (2014-2016)” *World Development Indicators*, Food and Agriculture Organization of the United States (FAO), [https://data.worldbank.org/indicator/AG.PRD.LVSK.XD](https://data.worldbank.org/indicator/AG.PRD.LVSK.XD). Accessed 31 Oct. 2025. **^3^World Bank.** “Pesticides use per capita” *World Development Indicators*, Food and Agriculture Organization of the United States (FAO), [https://data360.worldbank.org/en/indicator/FAO_RP_5172](https://data360.worldbank.org/en/indicator/FAO_RP_5172). Accessed 31 Oct. 2025. **^4^World Bank.** “Tertiary graduates from Ag, Vet, or Forestry programs (% of population)” *World Development Indicators*, The World Bank Group, [https://data.worldbank.org/indicator/SE.TER.GRAD.AG.ZS](https://data.worldbank.org/indicator/SE.TER.GRAD.AG.ZS). Accessed 15 Aug. 2025. **^5^World Bank.** “Tertiary graduates from Healthcare or Welfare programs (% of population)” *World Development Indicators*, The World Bank Group, [https://data.worldbank.org/indicator/SE.TER.GRAD.AG.ZS](https://data.worldbank.org/indicator/SE.TER.GRAD.AG.ZS). Accessed 15 Aug. 2025. **^6^World Bank.** “Literacy rate, adult total (% of people ages 15 and above)” *World Development Indicators*, UN Educational, Scientific and Cultural Organization (UNESCO), [https://data.worldbank.org/indicator/SE.ADT.LITR.ZS?view=chart](https://data.worldbank.org/indicator/SE.ADT.LITR.ZS?view=chart). Accessed 31 Oct. 2025. **^7^World Bank.** “Government expenditure on education, total (% of government expenditure)”*World Development Indicators*, UN Educational, Scientific and Cultural Organization (UNESCO),[https://data.worldbank.org/indicator/SE.XPD.TOTL.GB.ZS](https://data.worldbank.org/indicator/SE.XPD.TOTL.GB.ZS). Accessed 31 Oct. 2025. **^8^World Bank.** “Current health expenditure (% of GDP)” *World Development Indicators*, UN Educational, Scientific and Cultural Organization (UNESCO), [https://data.worldbank.org/indicator/SH.XPD.CHEX.GD.ZS](https://data.worldbank.org/indicator/SH.XPD.CHEX.GD.ZS). Accessed 31 Oct. 2025. **^9^World Bank.** “Gini index” *World Development Indicators*, UN Educational, Scientific and Cultural Organization (UNESCO), [https://data.worldbank.org/indicator/SI.POV.GINI](https://data.worldbank.org/indicator/SI.POV.GINI). Accessed 31 Oct. 2025. **^10^World Bank.** “Poverty headcount ratio at national poverty lines (% of population)” *World Development Indicators*, The World Bank Group, [https://data.worldbank.org/indicator/SI.POV.GINI](https://data.worldbank.org/indicator/SI.POV.GINI). Accessed 31 Oct. 2025. **^11^World Bank.** “Access to electricity (% of population)” *World Development Indicators*, The World Bank Group, [https://data.worldbank.org/indicator/SI.POV.GINI](https://data.worldbank.org/indicator/SI.POV.GINI). Accessed 31 Oct. 2025. **^12^World Bank.** “Land area (sq. km)” *World Development Indicators*, Food and Agriculture Organization of the United Nations (FAO), [https://data.worldbank.org/indicator/AG.LND.TOTL.K2](https://data.worldbank.org/indicator/AG.LND.TOTL.K2). Accessed 31 Oct. 2025. **^13^World Bank.** “Urban population (% of total population)” *World Development Indicators*, World Urbanization Prospects United Nation (UN), [https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS](https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS). Accessed 31 Oct. 2025. **^14^World Bank.** “Employment in agriculture (% of total employment) (modeled ILO estimate)” *World Development Indicators*, ILO Modelled Estimates database (IOLEST) International Labour Organization (ILO), [https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS](https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS). Accessed 31 Oct. 2025. **^15^World Bank.** “NTD interventions, people requiring interentions against NTDS (number)” *World Health Organization,* The Global Health Observatory, [https://www.who.int/data/gho/data/indicators/indicator-details/GHO/reported-number-of-people-requiring-interventions-against-ntds#:~:text=In%202022%2C%201.62%20billion%20people,fewer%20than%20reported%20in%202021](https://www.who.int/data/gho/data/indicators/indicator-details/GHO/reported-number-of-people-requiring-interventions-against-ntds#:~:text=In%202022%2C%201.62%20billion%20people,fewer%20than%20reported%20in%202021). Accessed 31 Oct. 2025. **^16^SEDAC.** “Gridded Population of the World (GPW) v4” *Earthdata*, The Socioeconomic Data and Applications Center, [https://www.earthdata.nasa.gov/data/projects/gpw](https://www.earthdata.nasa.gov/data/projects/gpw). Accessed 15 Aug. 2025. **^17^GRDI.** “Global Gridded Relative Deprivation Index (GRDI) Subnational Human Development Index (SHDI)” *Earthdata*, The Socioeconomic Data and Applications Center, [https://www.earthdata.nasa.gov/data/catalog/sedac-ciesin-sedac-pmp-grdi-2010-2020-1.00](https://www.earthdata.nasa.gov/data/catalog/sedac-ciesin-sedac-pmp-grdi-2010-2020-1.00). Accessed 15 Aug. 2025. **^18^Gilbert et al. 2022.** “Global cattle distribution in 2015” *Food and Agriculture Organization*, Gridded Livestock of the World (GLW 4), [https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/LHBICE](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/LHBICE). Accessed 15 Aug. 2025. **^19^Tuanmu et al. 2015.** “Dissimilarity” *EarthEnv*, Global Habitat Heterogeneity, [https://www.earthenv.org/texture](https://www.earthenv.org/texture).  Accessed 15 Aug. 2025. **^20^Olson et al. 2004.** “Terrestrial Ecoregions of the World” *World Wildlife Fund - US*, Conservation Science Program, [https://www.earthenv.org/texture](https://www.earthenv.org/texture).  Accessed 15 Aug. 2025. **^21^Rubel et al. 2017.** “Köppen-Geiger Climate Classification” *Vetmed Uni Vienna*, Rubel and Kottek 2010 World Maps of Köppen-Geiger Climate Classification, [https://koeppen-geiger.vu-wien.ac.at/](https://koeppen-geiger.vu-wien.ac.at/). Accessed 15 Aug. 2025. **^22^ACLED.** “Total conflicts” *ACLED Conflict Exposure,* Raleigh et al 2023 Assessing and Mapping Global and Local Conflict Exposure, [https://www.earthenv.org/texture](https://www.earthenv.org/texture).  Accessed 15 Aug. 2025. **^23^ACLED.** “Percentage of the population exposed to conflict” *ACLED Conflict Exposure,* Raleigh et al 2023 Assessing and Mapping Global and Local Conflict Exposure, [https://www.earthenv.org/texture](https://www.earthenv.org/texture).  Accessed 15 Aug. 2025. **^24^IVSA.** “IVSA chapter presence” *International Veterinary Student Association*, Membership Directory, [https://www.ivsa.org/membership-directory/corporate](https://www.ivsa.org/membership-directory/corporate). Accessed 15 Aug. 2025.