The Resurgence of Measles, Mumps, and Pertussis

Papachrisanthou, Michelle M.; Davis, Renée L.

doi:10.1016/j.nurpra.2018.12.028

Cited by 12 publications

(12 citation statements)

References 25 publications

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“…The majority of these cases occurred in unvaccinated individuals [8][9][10]. From collapsing public health infrastructure [11] and lack of access to vaccines [4] to non-medical exemptions, e.g., religious beliefs [12,13], and the spread of fraudulent science [14-16], the precise reason individuals go unvaccinated are myriad; however, underlying all these mechanisms is the coupled transmission of two contagions, one biological and one-or more-social.Clearly, contagions never occur in a vacuum, instead pathogens and ideas interact with each other and with externalities such as host connectivity, behaviour, and mobility. Nevertheless, many biological contagions are still considered to be "simple", where infectious individuals transmit to susceptible individuals independently of anything else occurring around the individuals, susceptible and/or infectious, in question [17].…”

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confidence: 99%

“… 5 , 10 The majority of these cases occurred in unvaccinated individuals. 11 – 13 From collapsing public health infrastructure 14 and lack of access to vaccines 7 to non-medical exemptions, e.g., religious beliefs, 15 , 16 and the spread of fraudulent science, 17 – 19 the precise reason individuals go unvaccinated are myriad; however, underlying all these mechanisms is the coupled transmission of two contagions, one biological and one—or more—social.…”

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confidence: 99%

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Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement

2020

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From fake news to innovative technologies, many contagions spread via a process of social reinforcement, where multiple exposures are distinct from prolonged exposure to a single source. Contrarily, biological agents such as Ebola or measles are typically thought to spread as simple contagions. Here, we demonstrate that interacting simple contagions are indistinguishable from complex contagions. In the social context, our results highlight the challenge of identifying and quantifying mechanisms, such as social reinforcement, in a world where an innumerable amount of ideas, memes and behaviors interact. In the biological context, this parallel allows the use of complex contagions to effectively quantify the non-trivial interactions of infectious diseases.On September 27th 2016, the World Health Organization (WHO) declared that measles had been eliminated from the Americas [1]. Less than two years later, an outbreak of the disease in Venezuela sparked an epidemic across South America, which is ongoing and has sickened tens-of-thousands [2][3][4]. Concurrently, the number of measles cases has increased in all but one of the WHO regions [5], over 80,000 cases (with a hospitalisation rate >60%) occurred in the European Union [6], and the United States of America experienced 17 measles outbreaks [2,7]. The majority of these cases occurred in unvaccinated individuals [8][9][10]. From collapsing public health infrastructure [11] and lack of access to vaccines [4] to non-medical exemptions, e.g., religious beliefs [12,13], and the spread of fraudulent science [14-16], the precise reason individuals go unvaccinated are myriad; however, underlying all these mechanisms is the coupled transmission of two contagions, one biological and one-or more-social.Clearly, contagions never occur in a vacuum, instead pathogens and ideas interact with each other and with externalities such as host connectivity, behaviour, and mobility. Nevertheless, many biological contagions are still considered to be "simple", where infectious individuals transmit to susceptible individuals independently of anything else occurring around the individuals, susceptible and/or infectious, in question [17]. In complex contagions, however, the spreading mechanism explicitly depends on the context of transmission events, usually via the neighbourhood of the susceptible individuals, such that pairwise information becomes insufficient to model the transmission process [18,19]. For example, social reinforcement can lead to a transmission rate effectively proportional to the number of different infectious contacts to which a susceptible individual is exposed [20]. This mechanistic difference creates a false dichotomy, forcing us to choose the mechanism we think best describe the reality of a given contagion. In practice, the context of transmission events always matters.When modeling a contagion, the choice of mechanism is critical because simple and complex contagions tend to induce substantially different dynamics and can lead to incompatible conclusions about i...

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Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement

2020

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“…[2][3][4][5][6] Vaccine hesitancy fueled by misinformation campaigns has often been a threat to sufficient vaccine coverage over past decades, sometimes leading to resurgence of vaccine-preventable diseases. [7][8][9] This has led the World Health Organization to recognize vaccine hesitancy as a major threat to global health in 2019. 10 International efforts to urgently deliver a safe and effective vaccine against COVID-19 have been faced with a growing anti-vaccination movement amplified by social media since the early phases of the pandemic, with the potential to negatively impact vaccination uptake in populations exposed to these campaigns.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Vaccination acceptance in the canton of Geneva: A Cross-Sectional Population-Based Study

Wisniak

Baysson

Pullen

et al. 2021

Preprint

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Objective This study aimed to assess acceptance of COVID-19 vaccination as well as its sociodemographic and clinical determinants in a general population sample three months after the launch of the vaccination program in Switzerland. Methods In March 2021, an online questionnaire on vaccination acceptance was proposed to adults included in a longitudinal cohort study of previous population-based serosurveys carried out in the canton of Geneva. Questions were asked about COVID-19 vaccination acceptance, reasons of acceptance or refusal, and attitudes about vaccination in general. Data on demographic (age, sex, education, income, professional status, living conditions) and health-related characteristics (having a chronic disease, COVID-19 diagnosis, smoking status) were assessed at inclusion in the cohort (December 2020). Results Overall, 4067 participants (completion rate of 77.4%) responded to the survey between March 17 and April 1, 2021. The mean age of respondents was 53.3 years and 56.0% were women. Most had completed tertiary education (64.7%) and over 60% were currently professionally active. At the time of the survey, 17.2% of respondents had already been vaccinated with at least one dose or had made an appointment to get vaccinated, and an additional 58.5% intended or rather intended to get vaccinated. The overall acceptance of COVID-19 vaccination was 75.7%, with a higher acceptance among men compared to women, older adults compared to younger adults, high-income individuals compared to those with a low income, participants living in urban and semi-urban areas compared to rural, and retirees and students compared to employed individuals. Acceptance was lower among individuals having completed apprenticeships and secondary education compared to those with tertiary education. The most common reasons reported by participants intending to get vaccinated were the desire to 'get back to normal', to protect themselves, their community and/or society, and their relatives or friends against the risk of infection by SARS-CoV-2, as well as the desire to travel. Less than half (45.6%) of participants having children were willing or rather willing to have their children vaccinated against COVID-19 if it were recommended by public health authorities. Conclusion Although our study found a 75.7% acceptance of COVID-19 vaccination, there were noticeable socio-demographic disparities in vaccination acceptance. These data will be useful for public health measures targeting hesitant populations when developing health communication strategies. These results will be updated over time with a new release of the survey in autumn 2021.

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“… 5 , 6 Not all outbreaks from the last 2 decades have been due to emerging infections, however; notably, due to increasing vaccine hesitancy around the world, re -emerging diseases, such as measles and mumps, have experienced a resurgence as well. 7 , 8 …”

Section: Introductionmentioning

confidence: 99%

A generalizable data assembly algorithm for infectious disease outbreaks

Majumder

Rose

2021

JAMIA Open

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During infectious disease outbreaks, health agencies often share text-based information about cases and deaths. This information is rarely machine-readable, thus creating challenges for outbreak researchers. Here, we introduce a generalizable data assembly algorithm that automatically curates text-based, outbreak-related information and demonstrate its performance across 3 outbreaks. After developing an algorithm with regular expressions, we automatically curated data from health agencies via 3 information sources: formal reports, email newsletters, and Twitter. A validation data set was also curated manually for each outbreak, and an implementation process was presented for application to future outbreaks. When compared against the validation data sets, the overall cumulative missingness and misidentification of the algorithmically curated data were ≤2% and ≤1%, respectively, for all 3 outbreaks. Within the context of outbreak research, our work successfully addresses the need for generalizable tools that can transform text-based information into machine-readable data across varied information sources and infectious diseases.

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The Resurgence of Measles, Mumps, and Pertussis

Cited by 12 publications

References 25 publications

Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement

Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement

COVID-19 Vaccination acceptance in the canton of Geneva: A Cross-Sectional Population-Based Study

A generalizable data assembly algorithm for infectious disease outbreaks

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