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A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366). This special issue belongs to the section "Infectious Diseases".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 26964

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Special Issue Editor

Dr. Tzai-Hung Wen

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Department of Geography and Institute of Epidemiology and Preventive Medicine, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan
Interests: spatial–temporal epidemiology; geo-computation and spatial analysis; mathematical modeling for infectious diseases and collective behaviors

Special Issue Information

Dear Colleagues,

Tracking epidemic progression and predicting the transmission risk of infectious diseases involve complex spatial–temporal interactions among agents, host, and environment (epidemiologic triangles). Due to the rapid development of computational and sensing technology in the big data era, the technology of tracking infectious diseases has improved the possibility of collecting and integrating information, from the population to molecular scale, for depicting more comprehensive epidemic progression in time and space. Such techniques have become essential epidemiological investigation methods for detecting disease outbreaks and monitoring the spatial–temporal patterns of epidemics, also improving our understanding of the complex interactions in epidemiological triangles.

This Special Issue on “Tracking infectious diseases” aims to focus on methodological theories of tracking technology (e.g., statistical and mathematical modeling, machine learning and evolutionary algorithms, geospatial informatics, communication infrastructures, micro-sensors, mobile data, etc.) for disease control and their applications and ethical concerns for tracing the source of infection, and identifying the transmission risk of infectious disease, with the goal to build scientific understanding on how the improvement of tracking technology can provide valuable insights in disease surveillance and detecting emerging disease clusters in time and space.

We encourage the submission of original research, in the form of innovative and unconventional applications of methodological, technological, administrative or ethical perspectives on tracking infectious diseases, for example, data analytics in outbreak detection and disease control, developing new algorithms for predicting epidemic progression, Artificial Intelligence of Things (AIoT) in disease surveillance, environmental exposure assessment, and best practices in disease tracking.

Dr. Tzai-Hung Wen
Guest Editor

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Keywords

contact tracing
disease transmission
disease surveillance
statistical and mathematical modeling
spatial–temporal epidemiology
epidemiological investigation

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Published Papers (9 papers)

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Research

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14 pages, 4158 KiB

Open AccessArticle

An Integrative Explainable Artificial Intelligence Approach to Analyze Fine-Scale Land-Cover and Land-Use Factors Associated with Spatial Distributions of Place of Residence of Reported Dengue Cases

by Hsiu Yang, Thi-Nhung Nguyen and Ting-Wu Chuang

Trop. Med. Infect. Dis. 2023, 8(4), 238; https://doi.org/10.3390/tropicalmed8040238 - 20 Apr 2023

Cited by 6 | Viewed by 2913

Abstract

Dengue fever is a prevalent mosquito-borne disease that burdens communities in subtropical and tropical regions. Dengue transmission is ecologically complex; several environmental conditions are critical for the spatial and temporal distribution of dengue. Interannual variability and spatial distribution of dengue transmission are well-studied; however, the effects of land cover and use are yet to be investigated. Therefore, we applied an explainable artificial intelligence (AI) approach to integrate the EXtreme Gradient Boosting and Shapley Additive Explanation (SHAP) methods to evaluate spatial patterns of the residences of reported dengue cases based on various fine-scale land-cover land-use types, Shannon’s diversity index, and household density in Kaohsiung City, Taiwan, between 2014 and 2015. We found that the proportions of general roads and residential areas play essential roles in dengue case residences with nonlinear patterns. Agriculture-related features were negatively associated with dengue incidence. Additionally, Shannon’s diversity index showed a U-shaped relationship with dengue infection, and SHAP dependence plots showed different relationships between various land-use types and dengue incidence. Finally, landscape-based prediction maps were generated from the best-fit model and highlighted high-risk zones within the metropolitan region. The explainable AI approach delineated precise associations between spatial patterns of the residences of dengue cases and diverse land-use characteristics. This information is beneficial for resource allocation and control strategy modification. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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15 pages, 4614 KiB

Open AccessArticle

Potential Epidemic Vulnerability and Socioepidemiological Profile of SARS-CoV2 in the Brazilian Northeast Region

by Lohanna Valeska de Sousa Tavares, Antônio Júnior Alves Ribeiro and Denise Maria Christofolini

Trop. Med. Infect. Dis. 2023, 8(4), 192; https://doi.org/10.3390/tropicalmed8040192 - 27 Mar 2023

Viewed by 1440

Abstract

Background: COVID-19 is a significant public health problem that can have a negative impact, especially in vulnerable regions. Objective: This study aimed to provide evidence that could positively influence coping with COVID-19 based on the relationship between the potential epidemic vulnerability index (PEVI) and socioepidemiological variables. This could be used as a decision-making tool for the planning of preventive initiatives in regions with relevant vulnerability indices for the spread of SARS-CoV-2. Methodology: We performed a cross-sectional study, with the analysis of the population characteristics of COVID-19 cases associated with neighborhoods’ PEVIs in the conurbation region of Crajubar, northeastern Brazil, through the mapping of socioeconomic–demographic factors and spatial autocorrelation. Results: The PEVI distribution indicated low vulnerability in areas with high real estate and commercial value; as communities moved away from these areas, the vulnerability levels increased. As for the number of cases, three of the five neighborhoods with a high–high autocorrelation, and some other neighborhoods showed a bivariate spatial correlation with a low–low PEVI but also high–low with indicators that make up the PEVI, representing areas that could be protected by public health measures to prevent increases in COVID-19 cases. Conclusions: The impact of the PEVI revealed areas that could be targeted by public policies to decrease the occurrence of COVID-19. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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22 pages, 8239 KiB

Open AccessArticle

Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia

by Wei Chien Benny Chin and Chun-Hsiang Chan

Trop. Med. Infect. Dis. 2023, 8(2), 72; https://doi.org/10.3390/tropicalmed8020072 - 19 Jan 2023

Cited by 2 | Viewed by 2392

Abstract

COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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12 pages, 3615 KiB

Open AccessArticle

Contribution of Testing Strategies and Contact Tracing towards COVID-19 Outbreaks Control: A Mathematical Modeling Study

by Shu-Chen Kuo, Byron Fan, Hongye Zhu, Meng-Hsuan Wu, Fang-Jing Lee, Yu-Chieh Cheng, Hsiao-Yu Wu, Ya-Ting Hsu, Chao A. Hsiung, Shiow-Ing Wu, Wei J. Chen, Hung-Yi Chiou, Huey-Kang Sytwu and Hsiao-Hui Tsou

Trop. Med. Infect. Dis. 2022, 7(11), 376; https://doi.org/10.3390/tropicalmed7110376 - 14 Nov 2022

Cited by 3 | Viewed by 1848

Abstract

This modeling study considers different screening strategies, contact tracing, and the severity of novel epidemic outbreaks for various population sizes, providing insight into multinational containment effectiveness of emerging infectious diseases, prior to vaccines development. During the period of the ancestral SARS-Cov-2 virus, contact tracing alone is insufficient to achieve outbreak control. Although universal testing is proposed in multiple nations, its effectiveness accompanied by other measures is rarely examined. Our research investigates the necessity of universal testing when contact tracing and symptomatic screening measures are implemented. We used a stochastic transmission model to simulate COVID-19 transmission, evaluating containment strategies via contact tracing, one-time high risk symptomatic testing, and universal testing. Despite universal testing having the potential to identify subclinical cases, which is crucial for non-pharmaceutical interventions, our model suggests that universal testing only reduces the total number of cases by 0.0009% for countries with low COVID-19 prevalence and 0.025% for countries with high COVID-19 prevalence when rigorous contact tracing and symptomatic screening are also implemented. These findings highlight the effectiveness of testing strategies and contact tracing in reducing COVID-19 cases by identifying subclinical cases. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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12 pages, 3575 KiB

Open AccessArticle

Epidemiology of COVID-19 in Individuals under 18 Years Old in Cartagena, Colombia: An Ecological Study of the First 14 Months of the Pandemic

by Steev Loyola, Eder Cano-Pérez, Jaison Torres-Pacheco, Dacia Malambo-Garcia, Ruben Gomez and Doris Gomez-Camargo

Trop. Med. Infect. Dis. 2022, 7(6), 107; https://doi.org/10.3390/tropicalmed7060107 - 15 Jun 2022

Cited by 2 | Viewed by 2268

Abstract

The epidemiology of the coronavirus disease (COVID-19) has been scarcely described in individuals under 18 years old, particularly during the first months of the pandemic. The study aimed to describe the COVID-19 epidemiology in the Colombian department of Bolívar from March 2020 to April 2021 among individuals under 18 years. Furthermore, we explored whether the use of data generated by a Bolívar reference laboratory captures the departmental epidemiology. Two information sources were used; the national COVID-19 surveillance system and the Bolívar COVID-19 reference laboratory. In using a population-based ecological approach and information from confirmed symptomatic cases, epidemic curves and heat maps were constructed to assess the COVID-19 dynamics and patterns by sex, age, and residence (Cartagena vs. 45 other municipalities). The COVID-19 incidence was comparable between males and females but varied by age group, being higher in children aged 10 years and older. Cartagena had a significantly higher number of cases and experienced early epidemic peaks. Our analyses suggest that information generated by the reference laboratory does not capture the COVID-19 departmental epidemiology, despite conducting population-based surveillance across Bolívar. The study provides a retrospective characterization of the COVID-19 epidemiology in an understudied population and information that may be useful for future evidence-based responses. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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Review

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12 pages, 585 KiB

Open AccessEditor’s ChoiceReview

How Spatial Epidemiology Helps Understand Infectious Human Disease Transmission

by Chia-Hsien Lin and Tzai-Hung Wen

Trop. Med. Infect. Dis. 2022, 7(8), 164; https://doi.org/10.3390/tropicalmed7080164 - 2 Aug 2022

Cited by 17 | Viewed by 5028

Abstract

Both directly and indirectly transmitted infectious diseases in humans are spatial-related. Spatial dimensions include: distances between susceptible humans and the environments shared by people, contaminated materials, and infectious animal species. Therefore, spatial concepts in managing and understanding emerging infectious diseases are crucial. Recently, due to the improvements in computing performance and statistical approaches, there are new possibilities regarding the visualization and analysis of disease spatial data. This review provides commonly used spatial or spatial-temporal approaches in managing infectious diseases. It covers four sections, namely: visualization, overall clustering, hot spot detection, and risk factor identification. The first three sections provide methods and epidemiological applications for both point data (i.e., individual data) and aggregate data (i.e., summaries of individual points). The last section focuses on the spatial regression methods adjusted for neighbour effects or spatial heterogeneity and their implementation. Understanding spatial-temporal variations in the spread of infectious diseases have three positive impacts on the management of diseases. These are: surveillance system improvements, the generation of hypotheses and approvals, and the establishment of prevention and control strategies. Notably, ethics and data quality have to be considered before applying spatial-temporal methods. Developing differential global positioning system methods and optimizing Bayesian estimations are future directions. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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Other

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16 pages, 1028 KiB

Open AccessEditor’s ChoiceSystematic Review

Under-Reporting of Tuberculosis Disease among Children and Adolescents in Low and Middle-Income Countries: A Systematic Review

by Alexandra R. Linn, Melanie M. Dubois and Andrew P. Steenhoff

Trop. Med. Infect. Dis. 2023, 8(6), 300; https://doi.org/10.3390/tropicalmed8060300 - 31 May 2023

Cited by 2 | Viewed by 2282

Abstract

Under-reporting of tuberculosis (TB) disease in children and adolescents is a significant global concern, as many children are missing from TB notification data. A systematic literature review was conducted to understand the global reporting gap of child and adolescent TB as well as current interventions to close this gap in Low- and Middle- Income Countries (LMIC). Our study found large and variable gaps in child and adolescent TB reporting, due to various factors. Interventions to close this gap exist but are limited. Future studies are necessary to improve global surveillance systems to improve TB care delivery for children and adolescents. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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11 pages, 1182 KiB

Open AccessBrief Report

A Case Report on a Human Bite Contact with a Rabid Honey Badger Mellivora capensis (Kromdraai Area, Cradle of Humankind, South Africa)

by Debrah Kgwana Mohale, Ernest Ngoepe, Munangatire Mparamoto, Lucille Blumberg and Claude Taurai Sabeta

Trop. Med. Infect. Dis. 2023, 8(4), 186; https://doi.org/10.3390/tropicalmed8040186 - 24 Mar 2023

Cited by 2 | Viewed by 2814

Abstract

In South Africa, rabies cycles are sustained by both domestic and wildlife host species. Despite the fact that the majority of human rabies cases are associated with dog bite exposures, wildlife species can potentially transmit rabies virus (RABV) infection to humans. In July 2021, a honey badger (Mellivora capensis) from the Kromdraai area (Gauteng Province) bit a dog on a small farm. The following day the same honey badger attacked three adults in the area, with one of the victims requiring hospitalization for management of her injuries. The honey badger was subsequently shot and the carcass submitted to the Agricultural Research Council-Onderstepoort Veterinary Research (ARC-OVR) for RABV diagnosis. A positive rabies diagnosis was confirmed and phylogenetic analysis of the amplified glycoprotein gene of the rabies virus demonstrated the virus to be of dog origin. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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17 pages, 3662 KiB

Open AccessSystematic Review

Updating the Insecticide Resistance Status of Aedes aegypti and Aedes albopictus in Asia: A Systematic Review and Meta-Analysis

by Ramdan Zulfa, Wei-Cheng Lo, Po-Ching Cheng, Martini Martini and Ting-Wu Chuang

Trop. Med. Infect. Dis. 2022, 7(10), 306; https://doi.org/10.3390/tropicalmed7100306 - 17 Oct 2022

Cited by 19 | Viewed by 4477

Abstract

Background: Aedes aegypti and Aedes albopictus are two important vectors of several important arboviruses, including the dengue, chikungunya, and Zika viruses. Insecticide application is an important approach to reduce vector abundance during Aedes spp.-borne outbreaks in the absence of effective vaccines and treatments. However, insecticide overuse can result in the development of resistance, and careful monitoring of resistance markers is required. Methods: This meta-analysis and systematic review explored the spatial and temporal patterns of insecticide resistance in Asia from 2000 to 2021. PubMed, Scopus, EbscoHost, and Embase were used to enhance the search capability. The random-effects model was applied for the 94 studies that met our inclusion criteria for qualitative synthesis and meta-analysis. Results: Four major insecticides were studied (malathion, dichlorodiphenyltrichloroethane, permethrin, and deltamethrin). Dichlorodiphenyltrichloroethane resistance rates were high in both Ae. aegypti and Ae. albopictus (68% and 64%, respectively). Conversely, malathion resistance was less prevalent in Ae. aegypti (3%), and deltamethrin resistance was less common in Ae. albopictus (2%). Ae. aegypti displayed consistently high resistance rates (35%) throughout the study period, whereas the rate of insecticide resistance in Ae. albopictus increased from 5% to 12%. The rates of the major kdr mutations F1534C, V1016G, and S989P were 29%, 26%, and 22%, respectively. Conclusions: Insecticide resistance in both Ae. aegypti and Ae. albopictus is widespread in Asia, although the rates vary by country. Continuous monitoring of the resistance markers and modification of the control strategies will be important for preventing unexpected outbreaks. This systematic review and meta-analysis provided up-to-date information on insecticide resistance in dengue-endemic countries in Asia. Full article

(This article belongs to the Special Issue Tracking Infectious Diseases)

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