Impact of Severe Weather Events on Public Health and Economy

Synopsis

Severe weather events pose significant threats to public health and the economy in the United States. This report analyzes the NOAA Storm Database to identify the most harmful events in terms of fatalities, injuries, and economic damage. We summarize and visualize the most hazardous weather events to assist policymakers in prioritizing disaster preparedness efforts.

Data Processing

Loading Required Libraries

library(data.table)
library(ggplot2)

options(scipen = 999)

Loading and Reading Data

The data is provided as a compressed CSV file (.bz2). We first load it into R as a data.table for efficient processing.

storm_data <- fread("C:/Users/tblo/Downloads/repdata_data_StormData.csv.bz2")

Cleaning and Preparing Data

We summarize fatalities, injuries, and economic damage by event type.

# Summarizing health impact
event_health <- storm_data[, .(
    total_fatalities = sum(FATALITIES, na.rm = TRUE),
    total_injuries = sum(INJURIES, na.rm = TRUE)
), by = EVTYPE]

# Sorting by most harmful event types
most_harmful <- event_health[order(-total_fatalities, -total_injuries)]

# Summarizing economic impact
mostdamage <- storm_data[, .(
    total_damage = sum(PROPDMG, na.rm = TRUE) + sum(CROPDMG, na.rm = TRUE)
), by = EVTYPE]

# Sorting by most damaging event types
mostdamage <- mostdamage[order(-total_damage)]

Results

Most Harmful Events to Population Health

ggplot(most_harmful[1:5], aes(x=reorder(EVTYPE, total_fatalities), y=total_fatalities)) +
  geom_bar(stat="identity", fill="steelblue") +
  coord_flip() +
  labs(title="Top 5 Most Harmful Event Types", x="Event Type", y="Total Fatalities") +
  theme_minimal()

print(event_health[1:5])

##           EVTYPE total_fatalities total_injuries
## 1:       TORNADO             5633          91346
## 2:     TSTM WIND              504           6957
## 3:          HAIL               15           1361
## 4: FREEZING RAIN                7             23
## 5:          SNOW                5             29

Events with the Greatest Economic Consequences

ggplot(mostdamage[1:5], aes(x=reorder(EVTYPE, total_damage), y=total_damage)) +
  geom_bar(stat="identity", fill="darkred") +
  coord_flip() +
  labs(title="Top 5 Most Economically Damaging Events", x="Event Type", y="Total Damage (in USD)") +
  theme_minimal()

Conclusion

Tornadoes cause the most fatalities and injuries in the U.S. but also the most economic damages. These insights can help policymakers allocate resources effectively for disaster preparedness.