Equal Graph Partitioning on Estimated Infection Network as an Effective Epidemic Mitigation Measure

Controlling severe outbreaks remains the most important problem in infectious disease area. With time, this problem will only become more severe as population density in urban centers grows. Social interactions play a very important role in determining how infectious diseases spread, and organization of people along social lines gives rise to non-spatial networks in which the infections spread. Infection networks are different for diseases with different transmission modes, but are likely to be identical or highly similar for diseases that spread the same way. Hence, infection networks estimated from common infections can be useful to contain epidemics of a more severe disease with the same transmission mode. Here we present a proof-of-concept study demonstrating the effectiveness of epidemic mitigation based on such estimated infection networks. We first generate artificial social networks of different sizes and average degrees, but with roughly the same clustering characteristic. We then start SIR epidemics on these networks, censor the simulated incidences, and use them to reconstruct the infection network. We then efficiently fragment the estimated network by removing the smallest number of nodes identified by a graph partitioning algorithm. Finally, we demonstrate the effectiveness of this targeted strategy, by comparing it against traditional untargeted strategies, in slowing down and reducing the size of advancing epidemics

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Abstract Background Understanding the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may impact this risk. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed regression and classification models using NIRS on datasets of wild An. gambiae (s.l.) reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites. Results Regression models utilizing variable selection increased predictive accuracy over the more common full-spectrum partial least squares (PLS) approach for cross-validation of the datasets, validation, and independent test sets. Models produced from datasets that included the greatest range of mosquito samples (i.e. different sampling locations and times) had the highest predictive accuracy on independent testing sets, though overall accuracy on these samples was low. For classification, we found that intramodel accuracy ranged between 73.5–97.0% for grouping of mosquitoes into “early” and “late” age classes, with the highest prediction accuracy found in laboratory colonized mosquitoes. However, this accuracy was decreased on test sets, with the highest classification of an independent set of wild-caught larvae reared to set ages being 69.6%. Conclusions Variation in NIRS data, likely from dietary, genetic, and other factors limits the accuracy of this technique with wild-caught mosquitoes. Alternative algorithms may help improve prediction accuracy, but care should be taken to either maximize variety in models or minimize confounders

Additional file 5: Table S4. of Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Full listing of ITS1–3 Blood-fed status, metadata, and spectral data. Each ITS is listed on a new tab of the .xlsx file. Abbreviations: BF, blood-fed; PBF, partially blood-fed; NBF, non-blood-fed; Loc, location and trapping method; Sporo: sporozoite (nulliparous with value of 1, positive with 2; for ITS3 nulliparous mosquitoes have a value of 1, parous value of 2). (XLSX 5810 kb

Additional file 9: Figure S3. of Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Correlation plot of ages of sporozoite-positive mosquitoes. The predicted ages of expected old, sporozoite-positive mosquitoes for each of the four algorithms are shown. Partial least squares compared to enpls, svmLinear, VCPA (a), enpls compared to svmLinear and VCPA (b), and svmLinear compared to VCPA (c) are shown. All models correlated at P < 0.0001 via Pearson’s r. (TIFF 434 kb

Le Courrier

03 octobre 18331833/10/03 (N276)

Additional file 1: Table S1. of Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Dataset numbers. Calibration Model sample size and collection locations of single (DS1-DS4), and multi-source (DS5-DS6) origin. Soumousso and Kodeni are located in southwestern Burkina Faso. (XLSX 10 kb

Additional file 2: Figure S1. of Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Example figure of selection of optimal number of variables for ensemble PLS. The lowest root mean squared error of cross-validation for the fewest number of variables was used for prediction of test sets. In this example, 300 variables was chosen, as it has lower error in cross-validation compared to other variable amounts (including the full spectra - 1851 variables). (TIFF 681 kb

Additional file 6: Table S5. of Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Blood-fed status on regression accuracy for ITS1. Root mean squared error of prediction for ITS1 with three algorithms. (XLSX 8 kb