Dot map cartograms for detection of infectious disease outbreaks: an application to Q fever, the Netherlands and pertussis, Germany

Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

BACKGROUND

We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT.

METHODS

Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords.

RESULTS

We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs.

CONCLUSION

Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

How Spatial Epidemiology Helps Understand Infectious Human Disease Transmission

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.

Then and Now: Investigating Anthropometrics and Child Mortality among Females in Malawi

Information on the concentration of body mass index and child death among females in Malawi, where the epidemics of weight gain have been disconcerting and preventable deaths among children linger, is limited. Therefore, the study examined the polarity of body mass index and the death of children among females. Using data from the Malawian Demographic and Health Survey from 2000 to 2015–2016, the study applied for the first time the index of concentration at the extremes and indirect demographic techniques to estimate the polarity of body mass index and child mortality among 65,499 females aged 15 to 49 years. The preponderance of obesity more than doubled from 2000 to 2015–2016 and was highest among females who were older (35–49 years), urban dwellers, rich, and located in districts within the central and southern regions. In addition, child survival was low among underweight, overweight, and obese females. While national-, regional-, and individual-level statistics are in development, these findings provide helpful information for health experts and other stakeholders to initiate appropriate age-region specific programs and interventions in Malawi, including targeting females in the high socio-economic bracket.

Reactions to geographic data visualization of infectious disease outbreaks: an experiment on the effectiveness of data presentation format and past occurrence information

OBJECTIVES

This study intended to compare the effectiveness of thematic maps with that of tabular data in comprehension and memory of risk magnitudes, with Zika virus (ZIKV) disease outbreaks in the United States as the subject matter. The study also aimed to examine the effects of data presentation format and past occurrence information on risk perception and risk avoidance intention.

STUDY DESIGN

This study used an experiment.

METHODS

Each participant was randomly assigned to view ZIKV disease 2017 incidence data presented in one of the three formats: a choropleth map, a graduated-circle map, and a table, after which they answered questions about comprehension and memory of risk magnitudes. Each participant was then randomly assigned to view or not to view incidence data of the previous occurrence of ZIKV outbreaks in 2016, after which they answered questions about risk perception and risk avoidance intention.

RESULTS

The results revealed the effectiveness of thematic maps over tabular data in comprehension, risk perception, and risk avoidance intention. Compared to tabular data, the choropleth map led to a better comprehension of relative risk magnitudes, the graduated-circle map led to higher risk perception, and both thematic maps led to greater risk avoidance intention. In contrast, tabular data led to better recognition of absolute risk magnitudes than both thematic maps. In addition, past occurrence information enhanced risk perception and risk avoidance intention.

CONCLUSIONS

The findings reveal the importance of data presentation format in comprehension and memory of risk magnitudes. This can be attributed to the cognitive match between the information emphasized in the presentation and that required by the tasks. The findings also suggest that data presentation format and past occurrence information are important judgmental heuristics that help to form risk perception and risk avoidance intention.

Evolution of Rabies in South America and Inter-Species Dynamics (2009-2018)

Rabies is listed as one of the World Health Organisation's (WHO) Neglected Tropical Diseases Worldwide, with a significant impact in South America. This paper explores the dynamics of rabies cases in humans, pets (dogs and cats), livestock and wildlife (bats in particular) in South America during the period 2009-2018. The data used in this study were derived from the two main databases for rabies in South America: the OIE-WAHIS from the World Organisation for Animal Health (OIE) and PANAFTOSA's Regional Information System for the Epidemiological Surveillance of Rabies (SIRVERA). Being a neglected disease with possible underreporting in some areas, the reported rabies cases may not always represent the real disease burden. The analysis focuses on the evolution of the number of cases in time and their spatial distribution, as well as on the main source of infections in humans, determined by laboratory assays of the antigenic variant or through epidemiological investigations. Additionally, Generalised Linear Mixed Models (GLMM) were used to evaluate the risk factors associated with the occurrence of human cases. Our results show that the highest impact of the disease in terms of number of cases was reported on livestock, while the overall number of cases (in animals and humans) progressively decreased along the study period. The spatial distribution of rabies in livestock showed two main clusters in the north-western (mainly Colombia) and in the south-eastern part of the affected area (Brazil), and a third smaller cluster in Peru. A cluster in dogs was observed in Bolivia. Out of the 192 human cases reported during the study period, 70% of them were transmitted by bats. The number of human cases reported during the study period were significantly associated with the number of rabies cases reported in livestock, pets and wildlife. Despite the overall decreasing case report rate, the disease still represents a major animal and public health concern in South America, and new strategies for compiling systematic information, networking and education are needed, as well as the education and training of veterinary staff.

A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950

Severe dengue outbreaks (DOs) affect the majority of Asian and Latin American countries. Whether all DOs always occurred in sub-tropical and tropical areas (STTA) has not been verified. We downloaded abstracts by searching keywords “dengue (MeSH Major Topic)” from Pubmed Central since 1950, including three collections: country names in abstracts (CNA), no abstracts (WA), and no country names in abstracts (Non-CNA). Visualizations were created to present the DOs across countries/areas in STTA. The percentages of mentioned country names and authors’ countries in STTA were computed on the CNA and Non-CNA bases. The social network analysis was applied to highlight the most cited articles and countries. We found that (1) three collections are 3427 (25.48%), 3137 (23.33%), and 6884 (51.19%) in CNA, WA, and Non-CNA, respectively; (2) the percentages of 94.3% and 79.9% were found in the CNA and Non-CNA groups; (3) the most mentioned country in abstracts were India, Thailand, and Brazil; (4) most authors in the Non-CNA collections were from the United States, Brazil, and China; (5) the most cited article (PMID = 23563266) authored by Bhatt et al. had 2604 citations since 2013. Our findings provide in-depth insights into the DO knowledge. The research approaches are recommended for authors in research on other infectious diseases in the future, not just limited to the DO topic.

The Use of hx-index to compare research achievements for ophthalmology authors in Mainland China, Hong Kong, and Taiwan since 2010

BACKGROUND:

Ophthalmology authors in mainland China, Hong Kong, or Taiwan were interested in knowing their individual research achievements (IRAs). This study was to evaluate the most cited authors, institutes, and regions in the mainland, Hong Kong, and Taiwan in the field of ophthalmology in the recent 10 years using the hx-index and to display the result with visual representations.

METHODS:

Using the PubMed search engine to download data, we conducted an observational study of citation analyses in affiliated research institutes and regions (provinces/areas) of all ophthalmology authors since 2010. A total of 19,364 published articles from 22,393 authors in the mainland, Hong Kong, and Taiwan were analyzed. The x-index and the Kano model were complemental to the hx-index in identifying IRAs. A pyramid plot was used to illustrate the importance of the author-weighted scheme (AWS) used in evaluating IRAs in academics. The hx-index combining both advantages of the h and x-index was proposed to assess individual IRAs. Furthermore, we drew: 1. a choropleth map on Google Maps to visualize the differences of IRA among regions and 2. a visual display to present individual hx-indexes.

RESULTS:

There is a significant rise over time in the number of publications. The top-ranking regions in hx-index were Shanghai (26.82), Guangdong (25.82), and Beijing (25.81). We demonstrated that Dr Wu from Taiwan published 144 articles in PMC and used the example to explain the importance of AWS when IRAs were assessed.

CONCLUSIONS:

With an overall increase in publications in the field of ophthalmology, contributions assessed by hx-indexes and the AWS should be encouraged and promoted more in the future.

Whether productive authors using the national health insurance database also achieve higher individual research metrics: A bibliometric study

BACKGROUND

Many researchers use the National Health Insurance Research Database (HIRD) to publish medical papers and gain exceptional outputs in academics. Whether they also obtain excellent citation metrics remains unclear.

METHODS

We searched the PubMed database (http://www.ncbi.nlm.nih.gov/pubmed) using the terms Taiwan and HIRD. We then downloaded 1997 articles published from 2012 to 2016. An authorship-weighted scheme (AWS) was applied to compute coauthor partial contributions from the article bylines. Both modified x-index and author impact factor (AIF) proved complementary to Hirsch's h-index for calculating individual research achievements (IRA). The metrics from 4684 authors were collected for comparison. Three hundred eligible authors with higher x-indexes were located and displayed on Google Maps dashboards. Ten separate clusters were identified using social network analysis (SNA) to highlight the research teams. The bootstrapping method was used to examine the differences in metrics among author clusters. The Kano model was applied to classify author IRAs into 3 parts.

RESULTS

The most productive author was Investigator#1 (Taichung City, Taiwan), who published 149 articles in 2015 and included 803 other members in his research teams. The Kano diagram results did not support his citation metrics beyond other clusters and individuals in IRAs.

CONCLUSION

The AWS-based bibliometric metrics make individual weighted research evaluations possible and available for comparison. The study results of productive authors using HIRD did not support the view that higher citation metrics exist in specific disciplines.

Choropleth map legend design for visualizing the most influential areas in article citation disparities: A bibliometric study

BACKGROUND

Disparities in health outcomes across countries/areas are a central concern in public health and epidemiology. However, few authors have discussed legends that can be complemental to choropleth maps (CMs) and merely linked differences in outcomes to other factors like density in areas. Thus, whether health outcome rates on CMs showing the geographical distribution can be applied to publication citations in bibliometric analyses requires further study. The legends for visualizing the most influential areas in article citation disparities should have sophisticated designs. This paper illustrates the use of cumulative frequency (CF) map legends along with Lorenz curves and Gini coefficients (GC) to characterize the disparity of article citations in areas on CMs, based on the quantile classification method for classes.

METHODS

By searching the PubMed database (pubmed.com), we used the keyword "Medicine" [journal] and downloaded 7042 articles published from 1945 to 2016. A total number of 41,628 articles were cited in Pubmed Central (PMC). The publication outputs based on the author's x-index were applied to plot CM about research contributions. The approach uses two methods (i.e., quantiles and equal total values for each class) with CF legends, in order to highlight the difference in x-indices across geographical areas on CMs. GC was applied to observe the x-index disparities in areas. Microsoft Excel Visual Basic for Application (VBA) was used for creating the CMs.

RESULTS

Results showed that the most productive and cited countries in Medicine (Baltimore) were China and the US. The most-cited states and cities were Maryland (the US) and Beijing (China). Taiwan (x-index = 24.38) ranked behind Maryland (25.97), but ahead of Beijing (16.9). China earned lower disparity (0.42) than the US (0.49) and the rest of the world (0.53) when the GCs were applied.

CONCLUSION

CF legends, particularly using the quantile classification for classes, can be useful to complement CMs. They also contain more information than those in standard CM legends that are commonly used with other classification methods. The steps of creating CM legends are described and introduced. Bibliometric analysts on CM can be replicated in the future.