Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study
Objective: To determine the potential effect of environment variables on cutaneous leishmaniasis occurrence using time-series models and compare the predictive ability of seasonal autoregressive integrated moving average (SARIMA) models and Markov switching model (MSM). Methods: This descriptive stu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wolters Kluwer Medknow Publications
2021-01-01
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| Series: | Asian Pacific Journal of Tropical Medicine |
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| Online Access: | http://www.apjtm.org/article.asp?issn=1995-7645;year=2021;volume=14;issue=2;spage=83;epage=93;aulast=Rahmanian |
| _version_ | 1811276999896858624 |
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| author | Vahid Rahmanian Saied Bokaie Aliakbar Haghdoost Mohsen Barouni |
| author_facet | Vahid Rahmanian Saied Bokaie Aliakbar Haghdoost Mohsen Barouni |
| author_sort | Vahid Rahmanian |
| collection | DOAJ |
| description | Objective: To determine the potential effect of environment variables on cutaneous leishmaniasis occurrence using time-series models and compare the predictive ability of seasonal autoregressive integrated moving average (SARIMA) models and Markov switching model (MSM).
Methods: This descriptive study employed yearly and monthly data of 49 364 parasitologically-confirmed cases of cutaneous leishmaniasis in Isfahan province, located in the center of Iran from January 2000 to December 2019. The data were provided by the leishmaniasis national surveillance system, the meteorological organization of Isfahan province, and Iranian Space Agency for vegetation information. The SARIMA and MSM models were implemented to examine the environmental factors of cutaneous leishmaniasis epidemics.
Results: The minimum relative humidity, maximum relative humidity, minimum wind speed, and maximum wind speed were significantly associated with cutaneous leishmaniasis epidemics in different lags (P<0.05). Comparing SARIMA and MSM, Akaikes information criterion (AIC), and mean absolute percentage error (MAPE) in MSM were much smaller than SARIMA models (MSM: AIC=0.95, MAPE=3.5%; SARIMA: AIC=158.93, MAPE:11.45%).
Conclusions: SARIMA and MSM can be a useful tool for predicting cutaneous leishmaniasis in Isfahan province. Since cutaneous leishmaniasis falls into one of two states of epidemic and non-epidemic, the use of MSM (dynamic) is recommended, which can provide more information compared to models that use a single distribution for all observations (Box-Jenkins SARIMA model). |
| first_indexed | 2024-04-13T00:07:44Z |
| format | Article |
| id | doaj.art-352289c592b94af8b66345c3a0a8d40f |
| institution | Directory Open Access Journal |
| issn | 2352-4146 |
| language | English |
| last_indexed | 2024-04-13T00:07:44Z |
| publishDate | 2021-01-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Asian Pacific Journal of Tropical Medicine |
| spelling | doaj.art-352289c592b94af8b66345c3a0a8d40f2022-12-22T03:11:10ZengWolters Kluwer Medknow PublicationsAsian Pacific Journal of Tropical Medicine2352-41462021-01-01142839310.4103/1995-7645.306739Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series studyVahid RahmanianSaied BokaieAliakbar HaghdoostMohsen BarouniObjective: To determine the potential effect of environment variables on cutaneous leishmaniasis occurrence using time-series models and compare the predictive ability of seasonal autoregressive integrated moving average (SARIMA) models and Markov switching model (MSM). Methods: This descriptive study employed yearly and monthly data of 49 364 parasitologically-confirmed cases of cutaneous leishmaniasis in Isfahan province, located in the center of Iran from January 2000 to December 2019. The data were provided by the leishmaniasis national surveillance system, the meteorological organization of Isfahan province, and Iranian Space Agency for vegetation information. The SARIMA and MSM models were implemented to examine the environmental factors of cutaneous leishmaniasis epidemics. Results: The minimum relative humidity, maximum relative humidity, minimum wind speed, and maximum wind speed were significantly associated with cutaneous leishmaniasis epidemics in different lags (P<0.05). Comparing SARIMA and MSM, Akaikes information criterion (AIC), and mean absolute percentage error (MAPE) in MSM were much smaller than SARIMA models (MSM: AIC=0.95, MAPE=3.5%; SARIMA: AIC=158.93, MAPE:11.45%). Conclusions: SARIMA and MSM can be a useful tool for predicting cutaneous leishmaniasis in Isfahan province. Since cutaneous leishmaniasis falls into one of two states of epidemic and non-epidemic, the use of MSM (dynamic) is recommended, which can provide more information compared to models that use a single distribution for all observations (Box-Jenkins SARIMA model).http://www.apjtm.org/article.asp?issn=1995-7645;year=2021;volume=14;issue=2;spage=83;epage=93;aulast=Rahmanianleishmaniasis; climate factor; time series analysis; forecasting; iran |
| spellingShingle | Vahid Rahmanian Saied Bokaie Aliakbar Haghdoost Mohsen Barouni Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study Asian Pacific Journal of Tropical Medicine leishmaniasis; climate factor; time series analysis; forecasting; iran |
| title | Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study |
| title_full | Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study |
| title_fullStr | Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study |
| title_full_unstemmed | Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study |
| title_short | Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study |
| title_sort | predicting cutaneous leishmaniasis using sarima and markov switching models in isfahan iran a time series study |
| topic | leishmaniasis; climate factor; time series analysis; forecasting; iran |
| url | http://www.apjtm.org/article.asp?issn=1995-7645;year=2021;volume=14;issue=2;spage=83;epage=93;aulast=Rahmanian |
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