Networks characteristics of the French healthcare networks.

<p>Networks characteristics of the French healthcare networks.</p

The intercommunity networks of patient transfers.

<p>(a) The intercommunity network from the 18 detected general patient network Greedy-based communities named based on the French metropolitan regions they encompass. Edge size and color indicate the source community and number of patients discharged. (b) The intercommunity network from 113 Map Equation communities detected in the general network. The nodes of the networks represent the geographical center of hospitals within the shared community.</p

Regional clustering of communities detected with greedy algorithm.

<p>Network hospitals and patient trajectories of the healthcare network in France of (a) the general healthcare network, (b) the suspected-HAI healthcare network, and (c) the HAI-specific healthcare network. In the general healthcare network, 18 communities were detected by the community clustering algorithm. Four of the 18 communities identified by the algorithm combine hospitals from two regions each, such that the 22 geographical regions are mapped into 18 communities. The original 22 French metropolitan regions before they were reformed to 13 regions implemented in 2016 are shown to correspond to the 2014 data. For the HAI-specific and suspected-HAI networks, the algorithm detected a higher number of communities (36 and 21 communities respectively). The communities, which overlapped the same regional communities in the general network, were given the same color and the newly detected communities were given different colors.</p

Healthcare facility types among the general, suspected-HAI, and HAI-specific networks and their hub hospitals.

<p>Healthcare facility types among the general, suspected-HAI, and HAI-specific networks and their hub hospitals.</p

Network characteristics of the random patient networks.

<p>Network characteristics of the random patient networks.</p

Hospital rankings by degree, betweenness, and closeness across the networks.

<p>Hospitals in the HAI-specific network (HAISN) (n = 1266), suspected-HAI network (SHAIN) (n = 1975), and general network (GN) (n = 2063) are displayed vertically and plotted against their ranking by degree, betweenness, and closeness centrality measures (top row). Only the hospitals shared between the HAISN and GN or the SHAIN and GN were linked. The color gradient refers to the hospital ranking for each centrality measure and the line colors correspond to the rankings of the hospitals in the GN. We tested the differences in rankings by Wilcoxon rank sum test of an increasing subset of hospital degrees starting from the highest rank and adding each consecutive rank and retesting. The grey area represents the range where the HAISN or SHAIN differed from the general network hospital rankings. We chose rankings at random for the hospital degrees, betweenness, and closeness centrality measures for comparison (bottom row). All random rankings were statistically different across the centrality measures between the HAISN and GN and the SHAIN and GN shared hospitals.</p

One-way sensitivity analysis of the impact of changing the base case parameter value to low and high values on the incremental cost-effectiveness ratios (ICERs) for Scenarios 3 (high primaquine adherence) and 4 (low primaquine adherence) as compared to the baseline scenario for peri-urban Manaus, São Gabriel da Cachoeira, and Itaituba.

See Table 1 for the ranges used for this analysis. (TIF)</p

One-way sensitivity analysis of the impact of changing the base case parameter value to low and high values on the incremental cost-effectiveness ratios for Scenarios 1 (tafenoquine for adults) and 2 (tafenoquine for all) as compared to the baseline (7 day low-dose primaquine (0.5 mg/kg)) for peri-urban Manaus, São Gabriel da Cachoeira, and Itaituba.

Primaquine adherence is 66.7% for all. See Table 1 for the ranges used for this analysis.</p

Mean and 95% credible intervals from the probabilistic sensitivity analysis for disability-adjusted life-years (DALYs) averted, incremental costs, and incremental cost effectiveness ratios (ICERs).

Mean and 95% credible intervals from the probabilistic sensitivity analysis for disability-adjusted life-years (DALYs) averted, incremental costs, and incremental cost effectiveness ratios (ICERs).</p

Total overall cases, costs, DALYs, and ICERs for Brazil from 2020–2029.

Total overall cases, costs, DALYs, and ICERs for Brazil from 2020–2029.</p