Climate stress impacts on livestock health: implications for farming livelihoods and animal disease in Karnataka, India

Adam Eskdale, Mahmoud El-Tholth, Jonathan Paul, Jayant Desphande, Jennifer Cole

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Understanding the impact of climate change on livestock health is critical to safeguarding global food supplies, economies, and farming livelihoods. We evidence, through exploration of secondary data informed by a rapid ethnographic assessment (REA) of farming livelihoods in Karnataka, India, that both precipitation and vapour pressure are key climate variables relating to outbreaks of haemorrhagic septicaemia (HS), anthrax (AX), and black quarter (BQ) across the Indian state of Karnataka.

Our research emerged from two projects that intended to address drivers of Antimicrobial Resistance (AMR) in India, but which were curtailed by the COVID-19 restrictions on fieldwork. Nonetheless, farmers’ insights and lived experience led to an exploration of the suspected role of climate change on animal ill-health. This led us to develop a risk classification tool that assesses how disease risk varies in Karnataka at present and in possible future scenarios. Despite relatively limited epidemiological data (from the NADRES-2 database), clear relationships between bacterial disease and high-risk zones were defined in the region. Risk maps were constructed using open-source climate data (Climate Research Unit (CRU) TS 4.5 dataset).

We identify temperature and maximum temperature to be negatively correlated with HS, AX and BQ, indicating that regions experiencing a cool (but still hot) climate with increasingly wetter, more humid conditions are at high risk of future outbreaks. Principal component analyses revealed the South-West (SW) India monsoon and winter periods to be the most strongly correlated with HS, AX and BQ outbreaks. We identify vapour pressure, a proxy for humidity, as having a positive relationship with these specific livestock diseases. These relationships allowed us to classify climate-associated risk of bacterial disease outbreaks using a combination of gridded meteorological time series and epidemiological outbreak data covering the same region and timespan of 1987–2020.
Original languageEnglish
Article number2022.0009
Pages (from-to)1-16
Number of pages16
JournalCABI One Health
Issue number2022
Publication statusPublished - 7 Dec 2022


  • Epidemiological Modelling
  • Climate
  • India
  • Bacterial Disease
  • Antibiotics
  • Antimicrobial Resistance

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