A national surveillance of eosinophilic meningitis in Thailand
Introduction: Eosinophilic meningitis (EOM) is an emerging infectious disease worldwide. The most common cause of EOM is infection with Angiostrongylus cantonensis One possible method of monitoring and control of this infection is surveillance and prediction. There are limited data on national surve...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-11-01
|
| Series: | Parasite Epidemiology and Control |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405673122000368 |
| _version_ | 1811178175275728896 |
|---|---|
| author | Noppadol Aekphachaisawat Kittisak Sawanyawisuth Sittichai Khamsai Watchara Boonsawat Somsak Tiamkao Panita Limpawattana Wanchai Maleewong Chetta Ngamjarus |
| author_facet | Noppadol Aekphachaisawat Kittisak Sawanyawisuth Sittichai Khamsai Watchara Boonsawat Somsak Tiamkao Panita Limpawattana Wanchai Maleewong Chetta Ngamjarus |
| author_sort | Noppadol Aekphachaisawat |
| collection | DOAJ |
| description | Introduction: Eosinophilic meningitis (EOM) is an emerging infectious disease worldwide. The most common cause of EOM is infection with Angiostrongylus cantonensis One possible method of monitoring and control of this infection is surveillance and prediction. There are limited data on national surveillance and predictive models on EOM. This study aimed to develop an online surveillance with a predictive model for EOM by using the national database. Methods: We retrospectively retrieved reported cases of EOM from all provinces in Thailand and quantified them by month and year. Data were retrieved from Ministry of Public Health database. We developed a website application to explore the EOM cases in Thailand including regions and provinces using box plots. The website also provided the Autoregressive Integrated Moving Average (ARIMA) models and Seasonal ARIMA (SARIMA) models for predicting the disease cases from nation, region, and province levels. The suitable models were considered by minimum Akaike Information Criterion (AIC). The appropriate SARIMA model was used to predict the number of EOM cases. Results: From 2003 to 2021, 3330 EOM cases were diagnosed and registered in the national database, with a peak in 2003 (median of 22 cases). We determined SARIMA(1,1,2)(2,0,0)[12] to be the most appropriate model, as it yielded the fitted values that were closest to the actual data. A predictive surveillance website was published on http://202.28.75.8/sample-apps/NationalEOM/. Conclusions: We determined that web application can be used for monitoring and exploring the trend of EOM patients in Thailand. The predictive values matched the actual monthly numbers of EOM cases indicating a good fit of the predictive model. |
| first_indexed | 2024-04-11T06:13:56Z |
| format | Article |
| id | doaj.art-50af2469fe7c48afbeea79b3cf239d9c |
| institution | Directory Open Access Journal |
| issn | 2405-6731 |
| language | English |
| last_indexed | 2024-04-11T06:13:56Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Parasite Epidemiology and Control |
| spelling | doaj.art-50af2469fe7c48afbeea79b3cf239d9c2022-12-22T04:41:06ZengElsevierParasite Epidemiology and Control2405-67312022-11-0119e00272A national surveillance of eosinophilic meningitis in ThailandNoppadol Aekphachaisawat0Kittisak Sawanyawisuth1Sittichai Khamsai2Watchara Boonsawat3Somsak Tiamkao4Panita Limpawattana5Wanchai Maleewong6Chetta Ngamjarus7Central Library, Silpakorn University, Bangkok, ThailandDepartment of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; Correspondence to: Kittisak Sawanyawisuth, Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, ThailandDepartment of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, ThailandDepartment of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, ThailandDepartment of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, ThailandDepartment of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen, ThailandDepartment of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand; Correspondence to: Chetta Ngamjarus, Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen 40002, Thailand.Introduction: Eosinophilic meningitis (EOM) is an emerging infectious disease worldwide. The most common cause of EOM is infection with Angiostrongylus cantonensis One possible method of monitoring and control of this infection is surveillance and prediction. There are limited data on national surveillance and predictive models on EOM. This study aimed to develop an online surveillance with a predictive model for EOM by using the national database. Methods: We retrospectively retrieved reported cases of EOM from all provinces in Thailand and quantified them by month and year. Data were retrieved from Ministry of Public Health database. We developed a website application to explore the EOM cases in Thailand including regions and provinces using box plots. The website also provided the Autoregressive Integrated Moving Average (ARIMA) models and Seasonal ARIMA (SARIMA) models for predicting the disease cases from nation, region, and province levels. The suitable models were considered by minimum Akaike Information Criterion (AIC). The appropriate SARIMA model was used to predict the number of EOM cases. Results: From 2003 to 2021, 3330 EOM cases were diagnosed and registered in the national database, with a peak in 2003 (median of 22 cases). We determined SARIMA(1,1,2)(2,0,0)[12] to be the most appropriate model, as it yielded the fitted values that were closest to the actual data. A predictive surveillance website was published on http://202.28.75.8/sample-apps/NationalEOM/. Conclusions: We determined that web application can be used for monitoring and exploring the trend of EOM patients in Thailand. The predictive values matched the actual monthly numbers of EOM cases indicating a good fit of the predictive model.http://www.sciencedirect.com/science/article/pii/S2405673122000368Angiostrongylus cantonensisDisease controlSnailsSlugsTime series analysis |
| spellingShingle | Noppadol Aekphachaisawat Kittisak Sawanyawisuth Sittichai Khamsai Watchara Boonsawat Somsak Tiamkao Panita Limpawattana Wanchai Maleewong Chetta Ngamjarus A national surveillance of eosinophilic meningitis in Thailand Parasite Epidemiology and Control Angiostrongylus cantonensis Disease control Snails Slugs Time series analysis |
| title | A national surveillance of eosinophilic meningitis in Thailand |
| title_full | A national surveillance of eosinophilic meningitis in Thailand |
| title_fullStr | A national surveillance of eosinophilic meningitis in Thailand |
| title_full_unstemmed | A national surveillance of eosinophilic meningitis in Thailand |
| title_short | A national surveillance of eosinophilic meningitis in Thailand |
| title_sort | national surveillance of eosinophilic meningitis in thailand |
| topic | Angiostrongylus cantonensis Disease control Snails Slugs Time series analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2405673122000368 |
| work_keys_str_mv | AT noppadolaekphachaisawat anationalsurveillanceofeosinophilicmeningitisinthailand AT kittisaksawanyawisuth anationalsurveillanceofeosinophilicmeningitisinthailand AT sittichaikhamsai anationalsurveillanceofeosinophilicmeningitisinthailand AT watcharaboonsawat anationalsurveillanceofeosinophilicmeningitisinthailand AT somsaktiamkao anationalsurveillanceofeosinophilicmeningitisinthailand AT panitalimpawattana anationalsurveillanceofeosinophilicmeningitisinthailand AT wanchaimaleewong anationalsurveillanceofeosinophilicmeningitisinthailand AT chettangamjarus anationalsurveillanceofeosinophilicmeningitisinthailand AT noppadolaekphachaisawat nationalsurveillanceofeosinophilicmeningitisinthailand AT kittisaksawanyawisuth nationalsurveillanceofeosinophilicmeningitisinthailand AT sittichaikhamsai nationalsurveillanceofeosinophilicmeningitisinthailand AT watcharaboonsawat nationalsurveillanceofeosinophilicmeningitisinthailand AT somsaktiamkao nationalsurveillanceofeosinophilicmeningitisinthailand AT panitalimpawattana nationalsurveillanceofeosinophilicmeningitisinthailand AT wanchaimaleewong nationalsurveillanceofeosinophilicmeningitisinthailand AT chettangamjarus nationalsurveillanceofeosinophilicmeningitisinthailand |