Environmental and climatic impact on the infection and mortality of SARS-CoV-2 in Peru

  1. Victor J. Samillan
  2. Diana Flores-León
  3. Eduardo Rojas
  4. Brian R. Zutta

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Abstract

Objectives

The role of the environment and climate in the transmission and case fatality rates of SARS-CoV-2 is still being investigated a year into the pandemic. Elevation and air quality are believed to be significant factors in the development of the pandemic, but the influence of additional environmental factors remains unclear.

Methods

We explored the relationship between the cumulative number of infections and mortality cases with climate (temperature, precipitation, solar radiation, water vapor pressure, wind), environmental data (elevation, normalized difference vegetation index or NDVI, particulate matter at 2.5 μm or PM 2.5 and NO 2 concentration), and population density in Peru. We use confirmed cases of infection from 1,287 districts and mortality in 479 districts, we used Spearman’s correlations to assess the bivariate correlation between environmental and climatic factors with cumulative infection cases, cumulative mortality and case-fatality rate. We explored district cases within the ecozones of coast, sierra, high montane forest and lowland rainforest.

Results

Multiple linear regression models indicate elevation, mean solar radiation, air quality, population density and green vegetation cover, as a socioeconomic proxy, are influential factors in the distribution of infection and mortality of SARS-CoV-2 in Peru. Case-fatality rate was weakly associated with elevation.

Conclusions

Our results also strongly suggest that exposure to poor air quality is a significant factor in the mortality of individuals below the age of 30. We conclude that environmental and climatic factors do play a significant role in the transmission and case fatality rates in Peru, however further study is required to see if these relationships are maintained over time.

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  1. Version published to 10.1515/jbcpp-2021-0007
  2. ScreenIT

    SciScore for 10.1101/2020.09.16.20196170: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Climate and environmental data: A set of climate metrics were obtained from WorldClim version 2.1 (Fick & Hijmans, 2017), which presents a historical baseline from the years 1979 to 2000 and includes monthly temperature, rainfall, wind speed, and solar radiation.
    WorldClim
    suggested: (WorldClim, RRID:SCR_010244)
    Data analysis: We extracted the zonal statistics by district (i.e. average value per district polygon) of each of the climate, remotely sensed and population density layers using ArcPro (verison 2.2).
    ArcPro
    suggested: None
    We used SPSS 25.0 (IBM, USA) for all statistical analysis of the extracted values.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The limitations of this study are indicative of the asymptomatic nature of SARS-CoV-2 for many patients. It is currently unclear the magnitude of underestimation occurring at the present time and accurate numbers may not become available until widespread molecular testing is performed. Also, news reports indicate that the cumulative number of mortality may also be significantly underestimated due to the lack of testing and patient care in overwhelmed urban and rural hospitals, particularly during the peaks of SARS-CoV-2 infection. In conclusion, elevation is one of several factors that has determined the number of infections and mortality. Other significant factors include population density, air quality, solar radiation and NDVI, as a measure of both green cover and socioeconomic level. Poor air quality was the single most important factor to determine mortality below the age of 30. We also found that case fatality rate is modified, albeit weakly, by elevation, which is contrary to previously published findings. As more data becomes available, this study can be replicated to see if the relationship between SARS-CoV-2 and climatic and environmental factors are maintained over time.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.09.16.20196170v2 on medRxiv
  4. Version published to 10.1101/2020.09.16.20196170v1 on medRxiv