Country transition index based on hierarchical clustering to predict next COVID-19 waves

A close contact identification algorithm using kernel density estimation for the ship passenger health

COVID-19 has been spread globally, with ships posing a significant challenge for virus containment due to their close-quartered environments. The most effective method for preventing the spread of the virus currently involves tracking and physically isolating close contacts. In this paper, we propose the Close Contact Identification Algorithm (CCIA). The probability density of user location points may be higher in a certain spatial range such as a cabin where there are more location points. The characteristics of CCIA include using Kernel Density Estimation (KDE) to calculate the probability density of each user location point and seeking the maximum Euclidean distance between location points in each cluster for merging clusters. CCIA is capable of calculating the probability density of each location point, a feature that other clustering algorithms, such as Kmeans, Hierarchical, and DBSCAN, cannot achieve. The contribution of CCIA is using the probability density of each location point to identify close contacts in ship environments. The performance of CCIA shows more accurate clustering compared to Kmeans, Hierarchical, and DBSCAN. CCIA can effectively identify close contacts and enhance the capabilities of user devices in mitigating the spread of COVID-19 within ship environments.

Characterizing pandemic waves: A latent class analysis of COVID-19 spread across US counties

The spread of the COVID-19 pandemic is observed to follow the shape of "waves" (i.e., the rise and fall of population-adjusted daily new infection cases with time). Different geographic regions of the world have experienced different position and span of these waves over time. The presence and strength of these waves broadly characterize the dynamics of the pandemic spread in a given area, so their characterization is important to draw meaningful intervention and mitigation plans tailored for that area. In this paper, we propose a novel technique to represent the trend of COVID-19 spread as a sequence of a fixed-length text string defined on three symbols: R (rise), S (Steady), and F (fall). These strings, termed as trend strings, enabled us searching for specific patterns in them (such as for waves). After analyzing county-level infection data, we observe that, US counties-despite their wide variation in trend strings-can be grouped into a number of heterogeneous classes each of which might have a representative COVID spread pattern over time (in terms of presence and propensity of waves). To this end, we conduct a latent class analysis to cluster 3142 US counties into four distinct classes based on their wave characteristics for one year pandemic data (January 2020 to January 2021). We observe that counties in each class have distinct socio-demographics, location, and human mobility characteristics. In short summary, counties have differing number of waves (class 1 counties have only one wave and class 3 counties have three) and their positions also vary (class 1 had the wave later in the year whereas class 3 had waves throughout the year). We believe that this way of characterizing pandemic waves would provide better insights in understanding the complex dynamics of COVID-19 spread and its future evolution, and would, therefore, help in taking class-specific policy interventions.

Combining rank-size and k-means for clustering countries over the COVID-19 new deaths per million

This paper deals with the cluster analysis of selected countries based on COVID-19 new deaths per million data. We implement a statistical procedure that combines a rank-size exploration and a k-means approach for clustering. Specifically, we first carry out a best-fit exercise on a suitable polynomial rank-size law at an individual country level; then, we cluster the considered countries by adopting a k-means clustering procedure based on the calibrated best-fit parameters. The investigated countries are selected considering those with a high value for the Healthcare Access and Quality Index to make a consistent analysis and reduce biases from the data collection phase. Interesting results emerge from the meaningful interpretation of the parameters of the best-fit curves; in particular, we show some relevant properties of the considered countries when dealing with the days with the highest number of new daily deaths per million and waves. Moreover, the exploration of the obtained clusters allows explaining some common countries' features.

Perceived Usefulness of Telerehabilitation of Musculoskeletal Disorders: A Belgium-France Pilot Study during Second Wave of COVID-19 Pandemic

BACKGROUND

COVID-19 has affected the practice of physiotherapy, and telerehabilitation (TR) may be seen as an alternative model of care if it is accepted by patients and physiotherapists. This study investigates the perceived usefulness of TR and the intention to use it among physiotherapists and patients from Belgium and France concerned with musculoskeletal disorders (MSDs) during the pandemic period.

METHODS

An online questionnaire based on the technology-acceptance model was designed. Sociodemographic data were collected and Likert scales were proposed to assess perceived ease-of-use, perceived usefulness and intention to use TR. Data were collected between 17 January and 17 March 2021; 68 patients and 107 physiotherapists answered.

RESULTS

In total, 88% of patients and 76% physiotherapists had not used TR at the time they answered. Only 12% of patients and 1% of physiotherapists are willing to use TR, and 50% of physiotherapists think they will never use TR compared to 25% of patients. A total of 98% of participants agreed that they had a good mastery of the technological tools requested.

CONCLUSIONS

Physiotherapists are more reluctant to use TR than patients, regardless of convincing EBM results. This is related to their own representation of proper MSD management, which must include the use of hands-on techniques.