A mathematical framework of SMS reminder campaigns for pre- and post-diagnosis check-ups using socio-demographics: An in-silco investigation into breast cancer

Savchenko, Elizaveta; Rosenfeld, Ariel; Bunimovich-Mendrazitsky, Svetlana

doi:10.1016/j.seps.2024.102047

Socio-Economic Planning Sciences

2024

DOI: 10.1016/j.seps.2024.102047

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A mathematical framework of SMS reminder campaigns for pre- and post-diagnosis check-ups using socio-demographics: An in-silco investigation into breast cancer

Elizaveta Savchenko,

Ariel Rosenfeld,

Svetlana Bunimovich-Mendrazitsky

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2024

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Cited by 2 publications

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Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Lazebnik

2024

Soc. Netw. Anal. Min.

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Sexually transmitted diseases (STDs) are a group of pathogens infecting new hosts through sexual interactions. Due to its social and economic burden, multiple models have been proposed to study the spreading of pathogens. In parallel, in the ever-evolving landscape of digital social interactions, the pervasive utilization of dating apps has become a prominent facet of modern society. Despite the surge in popularity and the profound impact on relationship formation, a crucial gap in the literature persists regarding the potential ramifications of dating apps usage on the dynamics of STDs. In this paper, we address this gap by presenting a novel mathematical framework - an extended Susceptible-Infected-Susceptible (SIS) epidemiological model to elucidate the intricate interplay between dating apps engagement and the propagation of STDs. Namely, as dating apps are designed to make users revisit them and have mainly casual sexual interactions with other users, they increase the number of causal partners, which increases the overall spread of STDS. Using extensive simulation, based on real-world data, explore the effect of dating apps adoption and control on the STD spread. We show that an increased adoption of dating apps can result in an STD outbreak if not handled appropriately.

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Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Lazebnik

2024

Soc. Netw. Anal. Min.

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Mathematical modeling of BCG-based bladder cancer treatment using socio-demographics

Savchenko,

Rosenfeld,

Bunimovich-Mendrazitsky

2023

Sci Rep

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Cancer is one of the most widespread diseases around the world with millions of new patients each year. Bladder cancer is one of the most prevalent types of cancer affecting all individuals alike with no obvious “prototypical patient”. The current standard treatment for BC follows a routine weekly Bacillus Calmette-Guérin (BCG) immunotherapy-based therapy protocol which is applied to all patients alike. The clinical outcomes associated with BCG treatment vary significantly among patients due to the biological and clinical complexity of the interaction between the immune system, treatments, and cancer cells. In this study, we take advantage of the patient’s socio-demographics to offer a personalized mathematical model that describes the clinical dynamics associated with BCG-based treatment. To this end, we adopt a well-established BCG treatment model and integrate a machine learning component to temporally adjust and reconfigure key parameters within the model thus promoting its personalization. Using real clinical data, we show that our personalized model favorably compares with the original one in predicting the number of cancer cells at the end of the treatment, with $$14.8\%$$ 14.8 % improvement, on average.

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A mathematical framework of SMS reminder campaigns for pre- and post-diagnosis check-ups using socio-demographics: An in-silco investigation into breast cancer

Cited by 2 publications

References 67 publications

Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Mathematical model of dating apps’ influence on sexually transmitted diseases spread

Mathematical modeling of BCG-based bladder cancer treatment using socio-demographics

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