Heterogeneous contact networks in COVID-19 spreading: the role of social deprivation
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Abstract
We have two main aims in this paper. First we use theories of disease spreading on networks to look at the COVID-19 epidemic on the basis of individual contacts — these give rise to predictions which are often rather different from the homogeneous mixing approaches usually used. Our second aim is to look at the role of social deprivation, again using networks as our basis, in the spread of this epidemic. We choose the city of Kolkata as a case study, but assert that the insights so obtained are applicable to a wide variety of urban environments which are densely populated and where social inequalities are rampant. Our predictions of hotspots are found to be in good agreement with those currently being identified empirically as containment zones and provide a useful guide for identifying potential areas of concern
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SciScore for 10.1101/2020.05.01.20087387: (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: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Potential Limitations: Without access to data on individual contact networks, we are limited to household sizes as measures of degree distributions, which they are only under (difficult to implement) conditions of strict lockdown. From this point of view, the level of agreement between our predictions and empirical data on containment …
SciScore for 10.1101/2020.05.01.20087387: (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: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Potential Limitations: Without access to data on individual contact networks, we are limited to household sizes as measures of degree distributions, which they are only under (difficult to implement) conditions of strict lockdown. From this point of view, the level of agreement between our predictions and empirical data on containment zones is indeed remarkable. However, we assert that our results should be interpreted qualitatively rather than quantitatively as a means of highlighting the difference between predictions arising from heterogeneous and homogeneous contact networks; for example, our predictions for Tc show clearly that contact network heterogeneity causes infections to spread much more rapidly than might be imagined on the basis of homogeneous theories. Another limitation arises from the availability of data on slums. In [11], 800 slums in Kolkata were studied via sampling methods, without any information on their exact location. We have therefore had to study the slums collectively, without any information on where exactly, and how extensive, they are in any particular area. The best that we have been able to do is, via census statistics on the percentage of slums per ward [9], compute the ward-based slum statistics to give a qualitative estimate of the ward-based Tc. Obviously, the approximation involved in doing this, i.e. treating the slums per ward as a contiguous unit when they are in fact distributed, is considerable, but in the absence of data, this is a...
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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