$N_{trade}$ report"
In qPRAentry: Quantitative Pest Risk Assessment at the Entry Step

knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE,
                      fig.pos = 'h',
                      fig.align = 'center',
                      fig.height = 3,
                      fig.width = 4)

#Available variables

time_period <- params$time_period
units <- params$units
nuts_yr <- params$nuts_yr
Nt <- params$Nt_result
Nt_redist <- params$Nt_redist
data_redistribution <- params$data_redistribution
population_year <- params$population_year

Introduction

This report details the results of the $N_{trade}$ analysis performed using the $N_{trade}$ app of the \texttt{qPRAentry} package.

In the context of quantitative risk assessment of pest entry, $N_{trade}$ is defined as the potentially infected/infested quantity of commodities imported by a country from other third-countries where the pest of interest is present. This application is meant to calculate $N_{trade}$ in countries using the NUTS coding system (NUTS0) and redistribute this quantity to the regions (NUTS2) of the countries considered.

Calculation of $N_{trade}$

For a given country of interest $i$, $N_{trade_i}$ is calculated taking into account the quantity of commodity imported by country $i$ from third countries where the pest is present, and the internal trade of this commodity, i.e., export and import between country $i$ and other countries of interest $j$, with $j \neq i$. Thus, $N_{trade_i}$ is approached as:

$$ N_{trade_i} = ExtraPest_i - ExtraPest_i \sum_{j \neq i} R_{ij} + \sum_{j \neq i} ExtraPest_j R_{ji}, $$

where $ExtraPest_i$ and $ExtraPest_j$ are the quantity of commodity imported from third countries where the pest is present by country $i$ and country $j$, respectively. $R_{ij}$ and $R_{ji}$ represent the proportion of commodity exported from $i$ to $j$ ($IntraExp_{ij}$), and from $j$ to $i$ ($IntraExp_{ji}$), respectively, out of the total available commodity in the exporter country. This total available quantity is considered as the sum of the internal production of the country ($IP$) and the total quantity imported from third countries ($ExtraTotal$), regardless of whether the pest is present. Therefore, $R_{ij}$ and $R_{ji}$ can be defined as:

$$R_{ij} = \frac{IntraExp_{ij}}{IP_i + ExtraTotal_i},$$

$$R_{ji} = \frac{IntraExp_{ji}}{IP_j + ExtraTotal_j}.$$

Based on these proportions, the quantity of $ExtraPest_i$ re-exported from country $i$ to all countries $j$ is approximated by $ExtraPest_i \sum_{j \neq i} R_{ij}$, while the quantity of $ExtraPest_j$ re-exported from all countries $j$ to country $i$ is estimated as $\sum_{j \neq i} ExtraPest_j R_{ji}$.

$N_{trade}$ has been calculated in r units for the following time-period: r time_period.

if(length(time_period)>1){
  col_plot <- title_plot <- "Median"
}else{
  col_plot <- paste0("Ntrade_", time_period)
  title_plot <- time_period
}

p <- plot_nuts(Nt, "NUTS0", col_plot,
               nuts_level = 0, nuts_year = nuts_yr,
               title = bquote(N[trade] ~ " " ~ .(title_plot)), 
               legend_title = units) +
  xlim(-20, 40) + ylim(35,70) +
  theme_bw()+
  theme(
     plot.title = element_text(size = 14),
     legend.title = element_text(size = 12)
   ) 

print(p)

$N_{trade}$ redistribution to NUTS2

After calculating $N_{trade}$ at the country level (NUTS0), the next step involves redistributing these quantities to NUTS2 regions.

if(data_redistribution=="Human population"){
  data_text <- "human population data from Eurostat"
}else{
  data_text <- "user custom data"
}

For this analysis, $N_{trade}$ data were redistributed from NUTS0 to NUTS2 level proportionally to r data_text.

# population year/s:

if(data_redistribution=="Human population"){
  data_text <- "human population data from Eurostat"
  if(length(population_year)==1){
    population_year_text <- paste0("The selected year for human population data is ",
                                   population_year, ".")
  }else{
    population_year_text <- 
      paste0("The selected years for which the average human population will be 
             used as the basis for redistribution are: ", 
             paste0(population_year, collapse=", "), ".")
  }
}else{
  data_text <- "user custom data"
  population_year_text <- NULL
}

r population_year_text

plot_nuts(Nt_redist, "NUTS2", col_plot, 
          nuts_level = 2, nuts_year = nuts_yr,
          title = bquote(N[trade] ~ " " ~ .(title_plot)), 
          legend_title = units) +
  xlim(-20, 40) + ylim(35,70) +
  theme_bw()+
  theme(
     plot.title = element_text(size = 14),
     legend.title = element_text(size = 12)
   )