Modeling to predict cases of hantavirus pulmonary syndrome in Chile.
Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation t...
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ftdoajarticles:oai:doaj.org/article:e2c89214da0748e5b74ab650ad2885f3 2023-05-15T15:15:28+02:00 Modeling to predict cases of hantavirus pulmonary syndrome in Chile. Elaine O Nsoesie Sumiko R Mekaru Naren Ramakrishnan Madhav V Marathe John S Brownstein 2014-04-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0002779 https://doaj.org/article/e2c89214da0748e5b74ab650ad2885f3 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC3998931?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0002779 https://doaj.org/article/e2c89214da0748e5b74ab650ad2885f3 PLoS Neglected Tropical Diseases, Vol 8, Iss 4, p e2779 (2014) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2014 ftdoajarticles https://doi.org/10.1371/journal.pntd.0002779 2022-12-31T01:48:33Z Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes.Monthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001-2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001-2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions.We focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model.Instead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLoS Neglected Tropical Diseases 8 4 e2779 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Elaine O Nsoesie Sumiko R Mekaru Naren Ramakrishnan Madhav V Marathe John S Brownstein Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes.Monthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001-2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001-2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions.We focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model.Instead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS. |
format |
Article in Journal/Newspaper |
author |
Elaine O Nsoesie Sumiko R Mekaru Naren Ramakrishnan Madhav V Marathe John S Brownstein |
author_facet |
Elaine O Nsoesie Sumiko R Mekaru Naren Ramakrishnan Madhav V Marathe John S Brownstein |
author_sort |
Elaine O Nsoesie |
title |
Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
title_short |
Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
title_full |
Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
title_fullStr |
Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
title_full_unstemmed |
Modeling to predict cases of hantavirus pulmonary syndrome in Chile. |
title_sort |
modeling to predict cases of hantavirus pulmonary syndrome in chile. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2014 |
url |
https://doi.org/10.1371/journal.pntd.0002779 https://doaj.org/article/e2c89214da0748e5b74ab650ad2885f3 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 8, Iss 4, p e2779 (2014) |
op_relation |
http://europepmc.org/articles/PMC3998931?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0002779 https://doaj.org/article/e2c89214da0748e5b74ab650ad2885f3 |
op_doi |
https://doi.org/10.1371/journal.pntd.0002779 |
container_title |
PLoS Neglected Tropical Diseases |
container_volume |
8 |
container_issue |
4 |
container_start_page |
e2779 |
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