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Harnessing the Power of Data and Technology to Improve Infectious Disease Control

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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 (10 December 2022) | Viewed by 18685

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Special Issue Editors

Prof. Dr. Archie Clements

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Guest Editor

School of Biological Sciences, Queen’s University Belfast, Belfast BT9 5DL, UK
Interests: epidemiology; spatial analysis; helminths; tuberculosis; malaria

Prof. Dr. Colleen Lau

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Guest Editor

School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, QLD 4006, Australia
Interests: infectious disease epidemiology; emerging infectious diseases; neglected tropical diseases; travel medicine
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Daniel J. Weiss

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Guest Editor

Faculty of Health Sciences, Curtin University, Perth, WA 6102, Australia
Interests: spatial analysis; malaria; epidemiology; accessibility

Special Issue Information

Dear Colleagues,

The world is experiencing the convergence of a global pandemic, renewed global interest in infectious diseases, and the acceleration of the information age. Disease-relevant data are more readily available and abundant than ever. Despite this, decision-makers struggle to make evidence-informed decisions regarding public health interventions and the allocation of scarce healthcare resources, which has a deleterious impact on the effectiveness of their responses. This is because the data are not synthesized in a way that is readily accessible or useful, the sheer abundance of information presents a confusing picture and consumers of the data may not know where to start. Political factors may also interfere with data analysis, data sharing and information dissemination. Many actors with their own interests may present information in a certain way to achieve a particular objective that might not be aligned with the greater public good. Data come from a wide variety of sources (e.g., surveillance systems, research findings, social media, satellites, telecommunications) and in multiple formats (e.g., geospatial data), may be of variable quality, and can come from disparate and poorly linked systems. The rapid progression of infectious disease outbreaks means there often is not sufficient time to collate, evaluate and synthesize data and evidence for decision-making. There may not be sufficient capability within health authorities to analyze the data or the health system may be unable to mobilize resources in response to rapidly evolving new information. This Special Issue focuses on how advances in digital technology, data science and analytics can be better harnessed to optimize the use of data to inform decision-making for infectious disease control by health authorities, public health decision makers, clinicians and the general public. We invite submissions from data scientists, epidemiologists, clinicians, public health practitioners, social scientists, health informaticians, cybersecurity experts and researchers to provide different disciplinary perspectives regarding the opportunities, challenges and pitfalls of harnessing data in the information age for better public health decision-making.

Prof. Dr. Archie Clements
Prof. Dr. Daniel J. Weiss
Prof. Dr. Colleen Lau
Guest Editors

Manuscript Submission Information

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Keywords

data
statistical analysis
data visualization
modelling
computation
epidemiology
digital health
data security

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Published Papers (7 papers)

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15 pages, 3885 KiB

Open AccessEditor’s ChoiceArticle

Impacts on Human Movement in Australian Cities Related to the COVID-19 Pandemic

by Daniel J. Weiss, Tara F. Boyhan, Mark Connell, Kefyalew Addis Alene, Paulina A. Dzianach, Tasmin L. Symons, Camilo A. Vargas-Ruiz, Peter W. Gething and Ewan Cameron

Trop. Med. Infect. Dis. 2023, 8(7), 363; https://doi.org/10.3390/tropicalmed8070363 - 14 Jul 2023

Cited by 2 | Viewed by 1817

Abstract

No studies have yet examined high-resolution shifts in the spatial patterns of human movement in Australia throughout 2020 and 2021, a period coincident with the repeated enactment and removal of varied governmental restrictions aimed at reducing community transmission of SARS-CoV-2. We compared overlapping timeseries of COVID-19 pandemic-related restrictions, epidemiological data on cases and vaccination rates, and high-resolution human movement data to characterize population-level responses to the pandemic in Australian cities. We found that restrictions on human movement and/or mandatory business closures reduced the average population-level weekly movement volumes in cities, as measured by aggregated travel time, by almost half. Of the movements that continued to occur, long movements reduced more dramatically than short movements, likely indicating that people stayed closer to home. We also found that the repeated lockdowns did not reduce their impact on human movement, but the effect of the restrictions on human movement waned as the duration of restrictions increased. Lastly, we found that after restrictions ceased, the subsequent surge in SARS-CoV-2 transmission coincided with a substantial, non-mandated drop in human movement volume. These findings have implications for public health policy makers when faced with anticipating responses to restrictions during future emergency situations. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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12 pages, 2101 KiB

Open AccessEditor’s ChoiceArticle

Evaluating COVID-19-Related Disruptions to Effective Malaria Case Management in 2020–2021 and Its Potential Effects on Malaria Burden in Sub-Saharan Africa

by Paulina A. Dzianach, Susan F. Rumisha, Jailos Lubinda, Adam Saddler, Mauricio van den Berg, Yalemzewod A. Gelaw, Joseph R. Harris, Annie J. Browne, Francesca Sanna, Jennifer A. Rozier, Beatriz Galatas, Laura F. Anderson, Camilo A. Vargas-Ruiz, Ewan Cameron, Peter W. Gething and Daniel J. Weiss

Trop. Med. Infect. Dis. 2023, 8(4), 216; https://doi.org/10.3390/tropicalmed8040216 - 4 Apr 2023

Cited by 4 | Viewed by 2351

Abstract

The COVID-19 pandemic has led to far-reaching disruptions to health systems, including preventative and curative services for malaria. The aim of this study was to estimate the magnitude of disruptions in malaria case management in sub-Saharan Africa and their impact on malaria burden during the COVID-19 pandemic. We used survey data collected by the World Health Organization, in which individual country stakeholders reported on the extent of disruptions to malaria diagnosis and treatment. The relative disruption values were then applied to estimates of antimalarial treatment rates and used as inputs to an established spatiotemporal Bayesian geostatistical framework to generate annual malaria burden estimates with case management disruptions. This enabled an estimation of the additional malaria burden attributable to pandemic-related impacts on treatment rates in 2020 and 2021. Our analysis found that disruptions in access to antimalarial treatment in sub-Saharan Africa likely resulted in approximately 5.9 (4.4–7.2 95% CI) million more malaria cases and 76 (20–132) thousand additional deaths in the 2020–2021 period within the study region, equivalent to approximately 1.2% (0.3–2.1 95% CI) greater clinical incidence of malaria and 8.1% (2.1–14.1 95% CI) greater malaria mortality than expected in the absence of the disruptions to malaria case management. The available evidence suggests that access to antimalarials was disrupted to a significant degree and should be considered an area of focus to avoid further escalations in malaria morbidity and mortality. The results from this analysis were used to estimate cases and deaths in the World Malaria Report 2022 during the pandemic years. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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13 pages, 2679 KiB

Open AccessArticle

Real-Time Monitoring of Infectious Disease Outbreaks with a Combination of Google Trends Search Results and the Moving Epidemic Method: A Respiratory Syncytial Virus Case Study

by Dawei Wang, Andrea Guerra, Frederick Wittke, John Cameron Lang, Kevin Bakker, Andrew W. Lee, Lyn Finelli and Yao-Hsuan Chen

Trop. Med. Infect. Dis. 2023, 8(2), 75; https://doi.org/10.3390/tropicalmed8020075 - 19 Jan 2023

Cited by 4 | Viewed by 4069

Abstract

The COVID-19 pandemic has disrupted the seasonal patterns of several infectious diseases. Understanding when and where an outbreak may occur is vital for public health planning and response. We usually rely on well-functioning surveillance systems to monitor epidemic outbreaks. However, not all countries have a well-functioning surveillance system in place, or at least not for the pathogen in question. We utilized Google Trends search results for RSV-related keywords to identify outbreaks. We evaluated the strength of the Pearson correlation coefficient between clinical surveillance data and online search data and applied the Moving Epidemic Method (MEM) to identify country-specific epidemic thresholds. Additionally, we established pseudo-RSV surveillance systems, enabling internal stakeholders to obtain insights on the speed and risk of any emerging RSV outbreaks in countries with imprecise disease surveillance systems but with Google Trends data. Strong correlations between RSV clinical surveillance data and Google Trends search results from several countries were observed. In monitoring an upcoming RSV outbreak with MEM, data collected from both systems yielded similar estimates of country-specific epidemic thresholds, starting time, and duration. We demonstrate in this study the potential of monitoring disease outbreaks in real time and complement classical disease surveillance systems by leveraging online search data. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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19 pages, 1653 KiB

Open AccessEditor’s ChoiceArticle

Spatially Explicit Environmental Factors Associated with Lymphatic Filariasis Infection in American Samoa

by Morgan E. Lemin, Angela Cadavid Restrepo, Helen J. Mayfield and Colleen L. Lau

Trop. Med. Infect. Dis. 2022, 7(10), 295; https://doi.org/10.3390/tropicalmed7100295 - 12 Oct 2022

Viewed by 2209

Abstract

Under the Global Program to Eliminate Lymphatic Filariasis (LF) American Samoa conducted seven rounds of mass drug administration (MDA) between 2000 and 2006. Subsequently, the territory passed the WHO recommended school-based transmission assessment survey (TAS) in 2011/2012 (TAS-1) and 2015 (TAS-2) but failed in 2016, when both TAS-3 and a community survey found LF antigen prevalence above what it had been in previous surveys. This study aimed to identify potential environmental drivers of LF to refine future surveillance efforts to detect re-emergence and recurrence. Data on five LF infection markers: antigen, Wb123, Bm14 and Bm33 antibodies and microfilaraemia, were obtained from a population-wide serosurvey conducted in American Samoa in 2016. Spatially explicit data on environmental factors were derived from freely available sources. Separate multivariable Poisson regression models were developed for each infection marker to assess and quantify the associations between LF infection markers and environmental variables. Rangeland, tree cover and urban cover were consistently associated with a higher seroprevalence of LF-infection markers, but to varying magnitudes between landcover classes. High slope gradient, population density and crop cover had a negative association with the seroprevalence of LF infection markers. No association between rainfall and LF infection markers was detected, potentially due to the limited variation in rainfall across the island. This study demonstrated that seroprevalence of LF infection markers were more consistently associated with topographical environmental variables, such as gradient of the slope, rather than climatic variables, such as rainfall. These results provide the initial groundwork to support the detection of areas where LF transmission is more likely to occur, and inform LF elimination efforts through better understanding of the environmental drivers. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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9 pages, 1909 KiB

Open AccessArticle

Effect of the COVID-19 Pandemic on Lower Respiratory Tract Infection Determinants in Thai Hospitalized Children: National Data Analysis 2015–2020

by Rattapon Uppala, Phanthila Sitthikarnkha, Sirapoom Niamsanit, Sumitr Sutra, Kaewjai Thepsuthammarat, Leelawadee Techasatian, Nattachai Anantasit and Jamaree Teeratakulpisarn

Trop. Med. Infect. Dis. 2022, 7(8), 151; https://doi.org/10.3390/tropicalmed7080151 - 28 Jul 2022

Cited by 12 | Viewed by 2203

Abstract

Background: The COVID-19 outbreak emerged in January 2020 and remains present in 2022. During this period, nonpharmaceutical interventions (NPIs) have been used to reduce the spread of COVID-19 infection. Nationwide data analysis should be pushed as the new standard to demonstrate the impact of COVID-19 infection on other respiratory illnesses and the reliability of NPIs during treatment. Objective: This study aims to identify and compare the incidence of lower respiratory tract infections (LRTIs) among children in Thailand before and after the emergence of COVID-19. Methods: A retrospective study was carried out in hospitalized children under the age of 18 in Thailand from October 2015 to September 2020. The International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification, was used to identify patient diagnoses (ICD-10-TM). The data were extracted from the Universal Coverage Health Security Scheme Database. Results: A total of 1,610,160 admissions were attributed to LRTIs. The most common diagnosis was pneumonia (61.9%). Compared to the 2019 fiscal year, the number of hospitalizations due to LRTIs decreased by 33.9% in the 2020 fiscal year (COVID-19 period) (282,590 vs. 186,651). The incidence of all three diagnostic groupings was substantially lower in the pre- and post-COVID-19 eras, with a decrease of 28% in the pneumonia group (incidence rate ratio (IRR) = 0.72; 95% confidence interval (CI): 0.71 to 0.72), 44% in the bronchiolitis group (IRR = 0.56; 95% CI: 0.55 to 0.57), and 34% in the bronchitis group (IRR = 0.66; 95% CI: 0.65 to 0.67). Between fiscal years 2019 and 2020, the overall monthly cost of all hospitalizations for LRTIs decreased considerably (p value < 0.001). Conclusions: NPIs may decrease the number of pediatric hospitalizations related to LRTIs. All policies designed to prevent the spread of COVID-19 must be continually utilized to maintain the prevention of LRTIs. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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17 pages, 5398 KiB

Open AccessArticle

Temporal and Spatial Analysis Techniques as Potential Tools for Combating the HIV Epidemic among Young Brazilian Amazonian People: An Ecological Study

by Andrey Oeiras Pedroso, Dulce Gomes, Sara Melissa Lago Sousa, Glenda Roberta Oliveira Naiff Ferreira, Aline Maria Pereira Cruz Ramos, Sandra Helena Isse Polaro, Laura Maria Vidal Nogueira and Eliã Pinheiro Botelho

Trop. Med. Infect. Dis. 2022, 7(7), 137; https://doi.org/10.3390/tropicalmed7070137 - 16 Jul 2022

Cited by 5 | Viewed by 2392

Abstract

Background: The main goal of this study was to analyze the HIV epidemic temporally and spatially among young people living in Pará, Brazil, from 2007 to 2018. Methods: For the temporal analysis, we employed an integrated autoregression of moving averages model associated with the seasonal trend using the LOESS decomposition method, which allowed for predictions to be made. In the spatial analysis, the techniques of autocorrelation, spatial and spatio-temporal risk analysis, and geographically weighted regression were used. Results: During the study period, there were 8143 notifications of HIV/AIDS cases. The temporal prediction indicated a trend of growth in the incidence rate in the 20–24-year-old group from January 2019 to December 2022 and a trend of stability in the 15- to 19-year-old and 25- to 29-year-old groups. There was a territorial expansion of the HIV epidemic in Pará. Novo Progresso and the Metropolitan Region of Belém (RMB) were the zones with the highest spatial and spatio-temporal risk for HIV. Social determinants including the Basic Education Development Index, the number of physicians per 10,000 inhabitants, and the municipal high school abandonment rate in the municipalities were associated with the risk of HIV/AIDS among young people in Pará. Conclusions: To eliminate HIV among young people in Pará, the access to treatment, diagnosis, and preventive healthcare services should be expanded. Sexual and reproductive health education should be reinforced in schools and communities. Furthermore, it is necessary to promote social equity and fight HIV stigma. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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10 pages, 1592 KiB

Open AccessEditor’s ChoicePerspective

Spatial and Temporal Data Visualisation for Mass Dissemination: Advances in the Era of COVID-19

by Archie C. A. Clements

Trop. Med. Infect. Dis. 2023, 8(6), 314; https://doi.org/10.3390/tropicalmed8060314 - 9 Jun 2023

Cited by 2 | Viewed by 2438

Abstract

The COVID-19 pandemic is the first major pandemic of the digital age and has been characterised by unprecedented public consumption of spatial and temporal disease data, which can enable greater transparency and accountability of governments to the public for their public health decisions. A variety of state and non-state actors have collated and presented maps, charts, and plots of data related to the pandemic in both static and dynamic formats. In particular, there has been a proliferation of online dashboards presenting data related to the pandemic. The sources and types of information displayed have evolved rapidly during the pandemic, with a general trend towards providing more specialised information pertinent to specific aspects of epidemiology or disease control, as opposed simply to disease and death notifications. Limited evaluation of the quality of COVID-19 data visualisation tools has been conducted and significant effort now needs to be spent on standardisation and quality improvement of national and international data visualisation systems including developing common indicators, data quality assurance mechanisms and visualisation approaches, and building compatible electronic systems for data collection and sharing. The increasing availability of disease data for public consumption presents challenges and opportunities for government, media organisations, academic research institutions, and the general public. A key challenge is ensuring consistency and effectiveness of public health messaging to ensure a coordinated response and public trust in intervention strategies. Capitalising on opportunities for greater government accountability for public health decision-making, and more effective mobilisation of public health interventions, is predicated on the provision of accurate and timely information. Full article

(This article belongs to the Special Issue Harnessing the Power of Data and Technology to Improve Infectious Disease Control)

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