This code should reproduce Figure 1 in Dada N, Jupatanakul N, Minard G, Short SM, Akorli J, and Villegas LM (2020). Considerations for mosquito microbiome research from the Mosquito Microbiome Consortium

## Install packages

install.packages("tidyverse")
install.packages("europepmc")
install.packages("cowplot")

library(tidyverse)
library(europepmc)
library(cowplot)

## Scrape research trend data from Europe PMC archive

#### Note: the following code will collect the most recent data for the period 2000-2020. If you are running this code after 2020, or require data for a different range of time, adjust the values for period in the code chunk to your desired time range

Mosquito_microbiome_research_trend <- europepmc::epmc_hits_trend(query = "mosquito microbiome", period = 2000:2020)

## Plot research trend data

Mosquito_microbiome_research_trend %>%
ggplot(aes(x = factor(year), y = (query_hits))) +
geom_col(fill = "#660066", width = 0.65, alpha = 0.9) +
scale_y_continuous(expand = c(0, 0)) +
theme_minimal_hgrid(10) +
labs(x = "Year", y = "Number of Europe PMC articles") +
ggtitle("Interest in mosquito microbiome research over the past two decades")

## Acknowledgements

This code is adapted from Daniel S. Quintana’s code for visualizing research trends. Original code can be found here.