Evidence map›Paper›PMID 32994653›Full record

ArticleLandscape and urban planning2020

Covid-19 and rural landscape: The case of Italy.

Mauro Agnoletti, Simone Manganelli, Francesco Piras

Abstract read
In one paragraph

Article in Landscape and urban planning, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Ecosystem degradation and the spread of Covid-19.Environmental monitoring and assessment · 2023
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Perspective on the status and behaviour of SARS-CoV-2 in soil.Saudi journal of biological sciences · 2022
    Review
  8. Article
  9. Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?International journal of environmental research and public health · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mauro AgnolettiCULTLAB - School of Agriculture, University of Florence, Italy.
Simone ManganelliEuropean Central Bank, Germany.
Francesco PirasCULTLAB - School of Agriculture, University of Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Throughout the covid-19 emergency, health authorities have presented contagion data divided by administrative regions with no reference to the type of landscape, environment or development model. This study has been conducted to understand whether there is a correlation between the number of infections and the different rural landscapes of the country. Italy's rural landscape can be classified in four types, according to the intensity of energy inputs used in the agricultural process, socioeconomic and environmental features. Type A includes areas of periurban agriculture surrounding the metropolitan cities, type B areas of intensive agriculture with high concentration of agroindustry, type C hilly areas with highly diversified agriculture and valuable landscape, and type D high hills and mountains with forests and protected areas. Areas A and B are located in the plains, covering 21% of the territory and accounting for 57% of the population. They produce most of the added value, consume high levels of energy and represent the main source of pollution. Areas C and D cover 79% of the territory and 43% of the population. We find that provinces with 10% more type C and D areas exhibit on average 10% fewer cases of contagion. The result is statistically significant, after controlling for demographic, economic and environmental characteristics of the provinces. The pollution produced in more energy-intensive landscape has triggered an intense debate of how to ensure the economic competitiveness of Italian agriculture, without compromising environmental integrity or public health. Our findings speak to this debate, by suggesting that planning for more rural territory with lower energy inputs may come with the added benefit of new development opportunities and decreasing the exposure of the population to covid-19. Cost benefit-analyses should take into account that policies aimed at revitalizing more rural areas may reduce the economic impact of covid-19 and of potential future pandemics.

Identifiers

PMID32994653
PMCPMC7515565

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.