Simulating a Community Mental Health Service During the COVID-19 Pandemic: Effects of Clinician–Clinician Encounters, Clinician–Patient–Family Encounters, Symptom-Triggered Protective Behaviour, and Household Clustering
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Abstract
Objectives: Face-to-face healthcare, including psychiatric provision, must continue despite reduced interpersonal contact during the COVID-19 (SARS-CoV-2 coronavirus) pandemic. Community-based services might use domiciliary visits, consultations in healthcare settings, or remote consultations. Services might also alter direct contact between clinicians. We examined the effects of appointment types and clinician–clinician encounters upon infection rates.
Design: Computer simulation.
Methods: We modelled a COVID-19-like disease in a hypothetical community healthcare team, their patients, and patients' household contacts (family). In one condition, clinicians met patients and briefly met family (e.g., home visit or collateral history). In another, patients attended alone (e.g., clinic visit), segregated from each other. In another, face-to-face contact was eliminated (e.g., videoconferencing). We also varied clinician–clinician contact; baseline and ongoing “external” infection rates; whether overt symptoms reduced transmission risk behaviourally (e.g., via personal protective equipment, PPE); and household clustering.
Results: Service organisation had minimal effects on whole-population infection under our assumptions but materially affected clinician infection. Appointment type and inter-clinician contact had greater effects at low external infection rates and without a behavioural symptom response. Clustering magnified the effect of appointment type. We discuss infection control and other factors affecting appointment choice and team organisation.
Conclusions: Distancing between clinicians can have significant effects on team infection. Loss of clinicians to infection likely has an adverse impact on care, not modelled here. Appointments must account for clinical necessity as well as infection control. Interventions to reduce transmission risk can synergize, arguing for maximal distancing and behavioural measures (e.g., PPE) consistent with safe care.
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SciScore for 10.1101/2020.04.27.20081505: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Study limitations: The biological parameters we took for COVID-19 spread were estimates from the published literature and in some cases are subject to high uncertainty; likewise our estimates of initial and ongoing infection rates. Disease parameters were constant across subjects, other than symptomaticity given infection, which was stochastic. A paucity of contacts outside the household is highly atypical but corresponds to current UK policy, …
SciScore for 10.1101/2020.04.27.20081505: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Study limitations: The biological parameters we took for COVID-19 spread were estimates from the published literature and in some cases are subject to high uncertainty; likewise our estimates of initial and ongoing infection rates. Disease parameters were constant across subjects, other than symptomaticity given infection, which was stochastic. A paucity of contacts outside the household is highly atypical but corresponds to current UK policy, if not necessarily universal practice. The behavioural effect of symptoms upon transmission risk was modelled in the same way for household contacts as for clinician–patient contacts, which is unrealistic in that clinicians are more likely to have access to PPE and rules mandating its use. Clinicians’ households were not modelled and would tend to increase clinician infection rates (particularly if clinicians share a household). We also modelled a series of one-off patient assessments; many patients, of course, are seen repeatedly by their clinical teams, or see many different healthcare teams routinely. However, all these aspects were constant across conditions. More important are limitations relating to differences between conditions. In the “family contact” (e.g. home visit) condition, we made assumptions about the duration of contact with family members, including that this plausibly encompassed the degree of surface as well as airborne transmission, and we assumed clinicians were not fomite vectors for direct transfer of virus betw...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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