Climate influence the human leptospirosis cases in Brazil, 2007–2019: a time series analysis. (30th June 2021)
- Record Type:
- Journal Article
- Title:
- Climate influence the human leptospirosis cases in Brazil, 2007–2019: a time series analysis. (30th June 2021)
- Main Title:
- Climate influence the human leptospirosis cases in Brazil, 2007–2019: a time series analysis
- Authors:
- Costa, Anna Cecília Trolesi Reis Borges
Pereira, Carine Rodrigues
Sáfadi, Thelma
Heinemann, Marcos Bryan
Dorneles, Elaine Maria Seles - Abstract:
- Abstract: Background: Human leptospirosis is responsible for great losses and deaths, especially in developing countries, which can be mitigated by knowing the correct health indicators and climate influence on the disease. Methods: Leptospirosis cases and deaths, population and precipitation were recovered from different databases (2007–2019). Annual incidence, mortality and case fatality rates (CFRs) of human leptospirosis and average precipitation were calculated for Brazil and its regions. Time series analysis using an moving average with external variable (ARMAX) model was used to analyse the monthly contribution and precipitation influence over leptospirosis cases for each Brazilian region and for the whole country. A forecast model to predict cases for 2020 was created for Brazil. Results: Human leptospirosis exhibited heterogeneous distribution among Brazilian regions, with most cases occurring during the rainy season and precipitation influenced the disease occurrence in all regions but the South. The forecast model predicted 3276.99 cases for 2020 (mean absolute percentage error 14.680 and root mean square error 53.013). Considering the annual average for the period, the leptospirosis incidence was 1913 cases per 100 000 inhabitants, mortality was 0.168 deaths per 100 000 inhabitants and the CFR was 8.83%. Conclusions: The models built can be useful for planning leptospirosis surveillance and control actions for the whole country and its regions and, together withAbstract: Background: Human leptospirosis is responsible for great losses and deaths, especially in developing countries, which can be mitigated by knowing the correct health indicators and climate influence on the disease. Methods: Leptospirosis cases and deaths, population and precipitation were recovered from different databases (2007–2019). Annual incidence, mortality and case fatality rates (CFRs) of human leptospirosis and average precipitation were calculated for Brazil and its regions. Time series analysis using an moving average with external variable (ARMAX) model was used to analyse the monthly contribution and precipitation influence over leptospirosis cases for each Brazilian region and for the whole country. A forecast model to predict cases for 2020 was created for Brazil. Results: Human leptospirosis exhibited heterogeneous distribution among Brazilian regions, with most cases occurring during the rainy season and precipitation influenced the disease occurrence in all regions but the South. The forecast model predicted 3276.99 cases for 2020 (mean absolute percentage error 14.680 and root mean square error 53.013). Considering the annual average for the period, the leptospirosis incidence was 1913 cases per 100 000 inhabitants, mortality was 0.168 deaths per 100 000 inhabitants and the CFR was 8.83%. Conclusions: The models built can be useful for planning leptospirosis surveillance and control actions for the whole country and its regions and, together with the health indicators, revealed no uniform epidemiological situation of leptospirosis in Brazil. … (more)
- Is Part Of:
- Transactions of the Royal Society of Tropical Medicine and Hygiene. Volume 116:Number 2(2022)
- Journal:
- Transactions of the Royal Society of Tropical Medicine and Hygiene
- Issue:
- Volume 116:Number 2(2022)
- Issue Display:
- Volume 116, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 116
- Issue:
- 2
- Issue Sort Value:
- 2022-0116-0002-0000
- Page Start:
- 124
- Page End:
- 132
- Publication Date:
- 2021-06-30
- Subjects:
- ARMAX -- epidemiology -- modelling -- time series analysis -- zoonosis
Tropical medicine -- Periodicals
616.9883 - Journal URLs:
- http://trstmh.oxfordjournals.org/content/by/year ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/trstmh/trab092 ↗
- Languages:
- English
- ISSNs:
- 0035-9203
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9003.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25889.xml