Associations Between Environmental and Sociodemographic Data and Hepatitis‐A Transmission in Pará State (Brazil)

Leal, Philipe Riskalla; Guimarães, Ricardo José de Paula Souza e; Kampel, Milton

doi:10.1029/2020gh000327

Cited by 6 publications

(6 citation statements)

References 64 publications

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“…To verify the effectiveness of the methods, we apply three widely used quality indexes, including Root Mean Square Error (RMSE), Mean Absolute Percent Error (MAPE), Mean Absolute Error (MAE). RMSE is sensitive to the maximum or minimum errors in a group of data, and can well express the precision of measurement, as shown in the formula (15). MAPE is a relative error representation method and is also the most popular indicator for evaluating prediction performance, as shown in the formula (16).…”

Section: Model Evaluationmentioning

confidence: 99%

“…A large number of literature show that meteorological factors are related to hand foot mouth disease [11,12], COVID-19 [13,14] and other diseases. Some researchers suggested that rainfall has a certain impact on the spread of hepatitis A virus [15]. Kiook Baek [16] analyzed the association between temperature and precipitation and the incidence of hepatitis A in Seoul, which proved that meteorological factors have an impact on hepatitis A and are helpful to predict the incidence of hepatitis A.…”

Section: Introductionmentioning

confidence: 99%

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Deep learning models for hepatitis E incidence prediction leveraging meteorological factors

Feng

Cui

et al. 2023

PLoS ONE

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Background Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infectious diseases incidence is of great significance for public health organizations to prevent the spread of diseases. However, only using historical incidence data for prediction can not get good results. This study analyzes the influence of meteorological factors on the incidence of hepatitis E, which are used to improve the accuracy of incidence prediction. Methods We extracted the monthly meteorological data, incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We employ GRA method to analyze the correlation between the incidence and meteorological factors. With these meteorological factors, we achieve a variety of methods for incidence of hepatitis E by LSTM and attention-based LSTM. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results Duration of sunshine and rainfall-related factors(total rainfall, maximum daily rainfall) are more relevant to the incidence of hepatitis E than other factors. Without meteorological factors, we obtained 20.74%, 19.50% for incidence in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we obtained 14.74%, 12.91%, 13.21%, 16.83% for incidence, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.83%. Without meteorological factors, we achieved 20.41%, 19.39% for cases in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we achieved 14.20%, 12.49%, 12.72%, 15.73% for cases, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.92%. More detailed results are shown in results section of this paper. Conclusions The experiments show that attention-based LSTM is superior to other comparative models. Multivariate attention and temporal attention can greatly improve the prediction performance of the models. Among them, when all meteorological factors are used, multivariate attention performance is better. This study can provide reference for the prediction of other infectious diseases.

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Section: Model Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors

Feng

Cui

et al. 2023

PLoS ONE

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“…Os maiores consumos de água potável estão relacionados aos melhores Brazilian Journal of Health Review, Curitiba, v. 5, n. 6, p.24012-24029, nov./dec., 2022 indicadores socioeconômicos (DIAS et al 2010). O resultado disso é a desigual proporção em que as populações mais vulneráveis são acometidas por doenças de veiculação hídrica (LEAL et al 2021). Pois nesse cenário de crescimento urbano descontrolado que muitas periferias urbanas apresentam, com alta densidade demográfica, falta de acesso a serviços de saúde, falta de saneamento básico e de acesso à água potável proporcionam um cenário propício para uma alta de casos de doenças de veiculação hídrica como a Hepatite A e de doenças relacionadas ao acúmulo de água como a dengue (ALMEIDA et al 2020;LEAL et al 2021).…”

Section: Valores Socioeconômicos Atribuídosunclassified

A importância da água dentro do conceito de saúde única

Souza¹,

Silva²,

Pereira³

et al. 2022

Braz. J. Hea. Rev.

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A água é essencial para a sobrevivência e manutenção de todos os organismos vivos. Sua importância vai além da atuação como solvente universal e da representação prática da Saúde Única, possuindo impacto direto e indireto na saúde humana, animal e ambiental. O presente trabalho trata-se de uma revisão bibliográfica narrativa que aborda a água como recurso finito e escasso; os valores socioeconômicos atribuídos à água; a água na saúde humana e animal; e a relação água e meio ambiente. A água de consumo é de apenas 2,5% do total, sendo apenas 8% destinada para abastecimento urbano, enquanto que 23% é consumido, de diversas maneiras, apenas pela indústria. Sem contar que é uma commodity passiva de cobrança, deixando em segundo plano o consumo da população e priorizando a monetização. Contudo, a Organização Mundial da Saúde procurou estabelecer diretrizes que visam a padronização da qualidade de água distribuída e o Brasil buscou estabelecer parâmetros para avaliação da qualidade da água. Ademais, a relação homem-ambiente está em constante interação, impossível fazer sua desassociação. Logo, a fome, sede e falta de higiene são fatores que afetam a saúde, seja animal ou humana, e são consequência da mínima infraestrutura hídrica, sendo o investimento em saneamento básico, na educação e em políticas públicas de gestão o caminho para reverter essa realidade.

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“…In Brazil, cases of HAV infection increased during the rainy season (14). In state of Pará, Brazil, monthly accumulated precipitation was positively correlated with the incidence of HAV (15). Tosepu (16) found a strong relationship between HAV and weather change, particularly rainfall and floods, in several areas, such as Spain, India, China, and Egypt.…”

Section: Introductionmentioning

confidence: 99%

“…Various spatio-temporal analyses have been conducted to explore and understand the risk of HAV in terms of spatial and temporal structures. Gomez-Barroso et al (21) analyzed the space-time risk of HAV using standardized incidence ratios (SIR; the ratio between actual and expected cases) and the posterior probability of the smoothed relative risk (RR; the ratio of the outcome probability for the exposed group to the probability for the unexposed group) in Spain at the (15) investigated the association between environmental and socio-demographic data in HAV transmission in Pará State, Brazil, using various models, including generalized linear models, multilayer perceptron (MPL) deep-learning algorithm, gradient boost, decision tree, and histogram gradient boost (HGB). To reflect the spatial variation, the longitude and latitude of each municipality were used as covariates in the model.…”

Section: Introductionmentioning

confidence: 99%

Investigating the spatio-temporal variation of hepatitis A in Korea using a Bayesian model

Jeong

Choi²

2023

Front. Public Health

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Hepatitis A is a water-borne infectious disease that frequently occurs in unsanitary environments. However, paradoxically, those who have spent their infancy in a sanitary environment are more susceptible to hepatitis A because they do not have the opportunity to acquire natural immunity. In Korea, hepatitis A is prevalent because of the distribution of uncooked seafood, especially during hot and humid summers. In general, the transmission of hepatitis A is known to be dynamically affected by socioeconomic, environmental, and weather-related factors and is heterogeneous in time and space. In this study, we aimed to investigate the spatio-temporal variation of hepatitis A and the effects of socioeconomic and weather-related factors in Korea using a flexible spatio-temporal model. We propose a Bayesian Poisson regression model coupled with spatio-temporal variability to estimate the effects of risk factors. We used weekly hepatitis A incidence data across 250 districts in Korea from 2016 to 2019. We found spatial and temporal autocorrelations of hepatitis A indicating that the spatial distribution of hepatitis A varied dynamically over time. From the estimation results, we noticed that the districts with large proportions of males and foreigners correspond to higher incidences. The average temperature was positively correlated with the incidence, which is in agreement with other studies showing that the incidences in Korea are noticeable in spring and summer due to the increased outdoor activity and intake of stale seafood. To the best of our knowledge, this study is the first to suggest a spatio-temporal model for hepatitis A across the entirety of Korean. The proposed model could be useful for predicting, preventing, and controlling the spread of hepatitis A.

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Associations Between Environmental and Sociodemographic Data and Hepatitis‐A Transmission in Pará State (Brazil)

Cited by 6 publications

References 64 publications

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors

Deep learning models for hepatitis E incidence prediction leveraging meteorological factors

A importância da água dentro do conceito de saúde única

Investigating the spatio-temporal variation of hepatitis A in Korea using a Bayesian model

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