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Published November 21, 2022 | Version v1
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Dataset of scoping reviews on climate-disease publications for Lyme disease and cryptosporidiosis

  • 1. Stockholm University
  • 2. KTH Royal Institute of Technology

Description

The climate-disease relationship is complex, where multiple driver-pressure factors and interactions combine with climate change in determining the occurrence geographies and timings of various infectious diseases. However, studies often focus on just some selected factor(s) and interaction(s). Such focus choices may limit and bias our understanding and predictive capability of disease sensitivity to climate and other driver-pressure changes. To assess these research choices and identify possible remaining key gaps and biases, a scoping review is applied to climate-disease related publications for Lyme disease and cryptosporidiosis. 

This dataset includes two excel files for Lyme disease (“literature_search_LD_raw.xls”) and cryptosporidiosis (“literature_search_CY_raw.xls”) respectively, covering all the relevant information for further analysis. Each excel file contains three sheets named “Search”, “Filter”, and “Quantitative”. Contents of each sheet is explained as follows.

1. “Search”

Sheet “Search” listed all the publications found from the literature searches, including the information of publication year, title, DOI, and Authors. The searches were performed in Web of Science™ (WoS) and considered publications from 1 January 2000 to 10 February 2022. Search terms were (('borreliosis' OR 'Lyme disease') AND ('climate' OR 'climate change' OR 'climate variability')) for Lyme disease, ((‘cryptosporidiosis’ OR ‘cryptosporidium’ OR ‘crypto.’) AND (‘climate’ OR ‘climate change’ OR ‘climate variability’)) for cryptosporidiosis. The search yielded 555 publication results for Lyme disease and 185 for cryptosporidiosis.

2. “Filter”

Sheet “Filter” listed the inclusions and exclusions for searched publications, and categories each included publication belonging to. Excluded articles (marked as blank in column “Included”) are ones that: (i) do not consider both climate and disease; (ii) are for Lyme disease, but not about the Ixodes transmission of the Borrelia pathogen; (iii) are not written in English; and (iv) are not full-text open access. Included articles (marked as “x” in column “Included”) are further classified into following categories based on their focus: for Lyme disease, categories of publications include reviews (mentioning), reviews (specifically discussing), public awareness, mitigation, survey (implications), investigations, projections, and others; for cryptosporidiosis, categories include reviews (mentioning), reviews (specifically discussing), survey (implications), investigations, projections, and others. Articles belonging to any categories are marked as “x”.

3. “Quantitative”

Sheet “Quantitative” lists further information extracted from quantitative studies which are articles under category of investigations and projections in sheet “filter”. Further extracted information is from the methods section of each study or from the full text if necessary. The information includes transmission components, study region (if applicable), category of investigations or projections, included driver-pressure factors, and methods. Transmission components are reproduction host, transmission host, vector, and human for Lyme disease; animal reservoir, environmental reservoir, and human for cryptosporidiosis. Study region considers specific countries as the smallest scale for spatial resolution, so that smaller than whole-country study sites were counted as studies of the associated countries. Included driver-pressure factors are categorized as shown in Table 1, including main categories and their covered variables. Methods include laboratory/field experimentation/observation, statistical analysis, mechanistic modelling, and synthesis/meta-analysis.

Table 1. Categories of factors and variables within each factor category studied in the quantitative publications.

Category

Lyme disease

Cryptosporidiosis

Variable

Sub-variable

Variable

Sub-variable

Climate

Temperature

 

Temperature

 

Precipitation

 

Precipitation

 

Air humidity

 

Air humidity

 

Wind speed

 

Wind speed

 

Solar radiation

 

Solar radiation

 

Cloud cover

 

Extreme weather

Heavy rainfall, storms, extreme heat

Climate variability

The North Atlantic Oscillation (NAO)

Climate variability

The Indian Ocean Dipole (IOD), The El Niño-Southern Oscillation (ENSO)

 

 

Air pressure

 

Land factors

Ground properties

Temperature, soil features, litter depth

Ground properties

Soil features

Vegetation

Density, height, vegetation type, forest type, vegetation water content, the Normalized Difference Vegetation Index (NDVI), beech tree production, pine masting, growing stage

Vegetation

Vegetation type, the Normalized Difference Vegetation Index (NDVI)

Land use

Urban, agriculture, green cover, grazing, landscape fragmentation

Land use

Urban area, agriculture area

Terrestrial water factors

Surface water

Distance to coast, proximity to water source, river length, water-covered area

Stream flow and quality aspects

Turbidity, flow rate, aquifer type, pH, electrical conductivity, water level

 

Snow cover

 

Snow cover

 

 

Soil moisture

 

Soil moisture

 

 

Extreme hydrological events

Long-term drought index

Extreme hydrological events

Long droughts, flood frequency, flood extent (area), flood history (event)

 

Evapotranspiration

Potential evapotranspiration, actual evapotranspiration

Water resource facilities

Water supply, water treatment

 

Socioeconomics

 

Population density, awareness, behavior

 

Urbanization, population density, economic development, health care facilities, human behavior, age structure

 

Other

Disease seasonality

 

Disease seasonality

 

 

Location-related features

Latitude, longitude, altitude, day length, slope

Location-related features

Latitude, longitude, altitude

 

Wildfires

 

 

 

 

Biodiversity

 

 

 

 

Notes

This work was supported by the Nordforsk Centre of Excellence CLINF (grant number 76413).

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