Background Worldwide, dengue fever is the most common arboviral disease in humans with an estimated 50–100 million dengue infections annually. In the last four decades, there has been a substantial increase in dengue fever cases, which is thought to be driven by human population growth and movement, urbanization, climate change, and socioeconomic factors. Public health practitioners have long been interested in the relationship between dengue fever and local weather because of the well-documented role that weather plays in vector species proliferation. This relationship is particularly salient in Peru, because more than half of the population is at risk for dengue infection and regions of the country are particularly sensitive to El NiÃ±o Southern Oscillation and its widespread impact on local weather through atmospheric teleconnections. Methods We aimed to explore the association between reported dengue cases in Peru and demographic and environmental factors, over the time period 2000 to 2019. Our unit of analysis was administrative districts. In an exploratory, descriptive analysis, we examined the bivariate relationship between reported confirmed dengue cases and demographic and environmental variables. Based on these findings and biologic rationale, we used a multivariate analysis to examine the association between dengue cases and temperature, using the monthly number of confirmed dengue cases, basic demographic variables associated with districts and monthly average temperature and monthly average accumulated precipitation. In a secondary analysis, we examined the association between reported dengue fever cases and El NiÃ±o events accounting for district population, natural region designation, and number of healthcare facilities for the time period 2000 to 2019. Results We found that both temperature and precipitation were positively associated with higher dengue incidence. However, the effect of precipitation was not as great as the effect for temperature. Natural region classification was also found to play a role, but this could be a result of differences in temperature and precipitation. We also found that El NiÃ±o time periods, as defined by the Oceanic NiÃ±o Index were not significantly associated with increased dengue incidence across Peru. However, when the El NiÃ±o Coastal Index was used, there was an overall positive significant association between El NiÃ±o time periods and dengue incidence. Conclusion Findings from this study complement other studies on dengue and weather and increase our understanding of how changing environmental and human factors impact dengue fever cases in Peru. Additionally, our findings could potentially provide information useful to Peruvian health authorities for the prevention and control of dengue fever or future modeling studies.