inverse geographic distance matrix Search Results


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SafeGraph Inc infectivity matrix derived from safegraph fluxes truncated to geographical distances dc < 400 km
Infectivity Matrix Derived From Safegraph Fluxes Truncated To Geographical Distances Dc < 400 Km, supplied by SafeGraph Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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infectivity matrix derived from safegraph fluxes truncated to geographical distances dc < 400 km - by Bioz Stars, 2026-10
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SafeGraph Inc infectivity matrix derived from safegraph fluxes truncated to geographical distances
Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances <t>\documentclass[12pt]{minimal}</t> \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km . Local epidemic sizes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_a$$\end{document} T a are shown. One symbol is associated to one given community and one given day.
Infectivity Matrix Derived From Safegraph Fluxes Truncated To Geographical Distances, supplied by SafeGraph Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/inverse+geographic+distance+matrix/infectivity+matrix+derived+from+safegraph+fluxes+truncated+to+geographical+distances/pmc09509367-118-51-46
Average 90 stars, based on 1 article reviews
infectivity matrix derived from safegraph fluxes truncated to geographical distances - by Bioz Stars, 2026-10
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Esri inc geographic distance matrix
Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances <t>\documentclass[12pt]{minimal}</t> \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km . Local epidemic sizes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_a$$\end{document} T a are shown. One symbol is associated to one given community and one given day.
Geographic Distance Matrix, supplied by Esri inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/inverse+geographic+distance+matrix/geographic+distance+matrix/10__1111_slash_eff__12245-89-3-11
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geographic distance matrix - by Bioz Stars, 2026-10
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Gauch GmbH euclidean distance-based geographic distance matrix
Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances <t>\documentclass[12pt]{minimal}</t> \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km . Local epidemic sizes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_a$$\end{document} T a are shown. One symbol is associated to one given community and one given day.
Euclidean Distance Based Geographic Distance Matrix, supplied by Gauch GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/inverse+geographic+distance+matrix/euclidean+distance+based+geographic+distance+matrix/10__1016_slash_j__funeco__2023__101261-123-4-6
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euclidean distance-based geographic distance matrix - by Bioz Stars, 2026-10
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Image Search Results


Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km . Local epidemic sizes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_a$$\end{document} T a are shown. One symbol is associated to one given community and one given day.

Journal: Scientific Reports

Article Title: A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies

doi: 10.1038/s41598-022-19931-w

Figure Lengend Snippet: Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km . Local epidemic sizes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_a$$\end{document} T a are shown. One symbol is associated to one given community and one given day.

Article Snippet: Figure 5 Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km .

Techniques: Comparison, Infection, Derivative Assay, Transmission Assay

Limiting long-distance travels without local lockdown. ( a ) Only transmission rates for communities separated by a distance \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{ij} < d_c$$\end{document} d ij < d c are retained. ( b ) Daily new infections for increasing values of the cutoff distance. ( c ) Spatial visualization of the daily new infections using a cutoff \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c = {200}\;{\text {km}}$$\end{document} d c = 200 km . See also Movie .

Journal: Scientific Reports

Article Title: A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies

doi: 10.1038/s41598-022-19931-w

Figure Lengend Snippet: Limiting long-distance travels without local lockdown. ( a ) Only transmission rates for communities separated by a distance \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_{ij} < d_c$$\end{document} d ij < d c are retained. ( b ) Daily new infections for increasing values of the cutoff distance. ( c ) Spatial visualization of the daily new infections using a cutoff \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c = {200}\;{\text {km}}$$\end{document} d c = 200 km . See also Movie .

Article Snippet: Figure 5 Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km .

Techniques: Transmission Assay

Random-matrix properties and mitigation strategies. ( a ) Level spacing distribution (unfolded , – ) of infectivity matrices between 2020-03-01 and 2021-02-15 (pooled by 7-day windows). The solid lines denote the Wigner-Dyson and the Poisson statistics. The level distribution is shown in Fig. . ( b ) The epidemic size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Omega /\Omega _0$$\end{document} Ω / Ω 0 versus the relative number of cuts \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N_c/N/(N-1)$$\end{document} N c / N / ( N - 1 ) for the 3 mitigation methods: distance cutoff, bandwidth, and edge-betweenness centrality. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Omega _0$$\end{document} Ω 0 is the epidemic size for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N_c=0$$\end{document} N c = 0 . Level-spacing entropy S and epidemic size as a function of ( c ) the cutoff distance \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c$$\end{document} d c in the range 170-12,000 km, and ( d ) the half-bandwidth \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1{\le }B<1023$$\end{document} 1 ≤ B < 1023 .

Journal: Scientific Reports

Article Title: A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies

doi: 10.1038/s41598-022-19931-w

Figure Lengend Snippet: Random-matrix properties and mitigation strategies. ( a ) Level spacing distribution (unfolded , – ) of infectivity matrices between 2020-03-01 and 2021-02-15 (pooled by 7-day windows). The solid lines denote the Wigner-Dyson and the Poisson statistics. The level distribution is shown in Fig. . ( b ) The epidemic size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Omega /\Omega _0$$\end{document} Ω / Ω 0 versus the relative number of cuts \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N_c/N/(N-1)$$\end{document} N c / N / ( N - 1 ) for the 3 mitigation methods: distance cutoff, bandwidth, and edge-betweenness centrality. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Omega _0$$\end{document} Ω 0 is the epidemic size for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N_c=0$$\end{document} N c = 0 . Level-spacing entropy S and epidemic size as a function of ( c ) the cutoff distance \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c$$\end{document} d c in the range 170-12,000 km, and ( d ) the half-bandwidth \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1{\le }B<1023$$\end{document} 1 ≤ B < 1023 .

Article Snippet: Figure 5 Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km .

Techniques: Infection

Model for the spreading of SARS-CoV-2 in a network of communities in the USA. ( a ) One community i interacting with three other communities j , k and l , with the transmission rates \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{ij}$$\end{document} β ij , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{ik}$$\end{document} β ik and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{il}$$\end{document} β il respectively. ( b ) Infectivity matrix. ( c ) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=2^{10}$$\end{document} N = 2 10 communities in the USA. Each community aggregates a number of Census Block Groups (CBGs).

Journal: Scientific Reports

Article Title: A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies

doi: 10.1038/s41598-022-19931-w

Figure Lengend Snippet: Model for the spreading of SARS-CoV-2 in a network of communities in the USA. ( a ) One community i interacting with three other communities j , k and l , with the transmission rates \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{ij}$$\end{document} β ij , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{ik}$$\end{document} β ik and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta _{il}$$\end{document} β il respectively. ( b ) Infectivity matrix. ( c ) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=2^{10}$$\end{document} N = 2 10 communities in the USA. Each community aggregates a number of Census Block Groups (CBGs).

Article Snippet: Figure 5 Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km .

Techniques: Transmission Assay, Infection, Blocking Assay

Existence of a wave with nearest-neighbors-only interactions. ( a ) Equation is solved on a square lattice of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2^n \times 2^m$$\end{document} 2 n × 2 m sites. ( b ) Traveling front of infected individuals moving along the x direction (left to right). We took \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha = \beta = \gamma = {0.1}$$\end{document} α = β = γ = 0.1 , so that the rescaled recovery rate is \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\gamma } = \gamma / (a \beta ) = {0.2}$$\end{document} γ ~ = γ / ( a β ) = 0.2 . ( c ) The dynamics simulated for different values of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document} β . The position m ( t ) ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S(t, m(t))=(1 + S_\infty )/2$$\end{document} S ( t , m ( t ) ) = ( 1 + S ∞ ) / 2 ) of the wave is asymptotically linear in time, hence a constant velocity \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{v} = \sqrt{1-\tilde{\gamma }}$$\end{document} v ~ = 1 - γ ~ . ( d ) The simulated wave profiles (symbols) are in agreement with the profiles predicted by Eq. (solid lines). The corresponding S,I,R profiles are shown in Fig. . A simulation with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\gamma } = {0.2}$$\end{document} γ ~ = 0.2 is shown in Movie .

Journal: Scientific Reports

Article Title: A high-resolution flux-matrix model describes the spread of diseases in a spatial network and the effect of mitigation strategies

doi: 10.1038/s41598-022-19931-w

Figure Lengend Snippet: Existence of a wave with nearest-neighbors-only interactions. ( a ) Equation is solved on a square lattice of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2^n \times 2^m$$\end{document} 2 n × 2 m sites. ( b ) Traveling front of infected individuals moving along the x direction (left to right). We took \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha = \beta = \gamma = {0.1}$$\end{document} α = β = γ = 0.1 , so that the rescaled recovery rate is \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\gamma } = \gamma / (a \beta ) = {0.2}$$\end{document} γ ~ = γ / ( a β ) = 0.2 . ( c ) The dynamics simulated for different values of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document} β . The position m ( t ) ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S(t, m(t))=(1 + S_\infty )/2$$\end{document} S ( t , m ( t ) ) = ( 1 + S ∞ ) / 2 ) of the wave is asymptotically linear in time, hence a constant velocity \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{v} = \sqrt{1-\tilde{\gamma }}$$\end{document} v ~ = 1 - γ ~ . ( d ) The simulated wave profiles (symbols) are in agreement with the profiles predicted by Eq. (solid lines). The corresponding S,I,R profiles are shown in Fig. . A simulation with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tilde{\gamma } = {0.2}$$\end{document} γ ~ = 0.2 is shown in Movie .

Article Snippet: Figure 5 Comparison of the (fitted) model predictions with reported values using ( a ) the infectivity matrix derived from SafeGraph fluxes (same model as Fig. ), ( b ) an infectivity matrix with uniform transmission rates, and ( c ) the infectivity matrix derived from SafeGraph fluxes truncated to geographical distances \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$d_c < {400} \; \text{km}$$\end{document} d c < 400 km .

Techniques: Infection