Real-Time Assessment of Health-Care Requirements During the Zika Virus Epidemic in Martinique

Abstract

The spread of Zika virus in the Americas has been associated with a surge in Guillain-Barré syndrome (GBS) cases. Given the severity of GBS, territories affected by Zika virus need to plan health-care resources to manage GBS patients. To inform such planning in Martinique, we analyzed Zika virus surveillance and GBS data from Martinique in real time with a modeling framework that captured dynamics of the Zika virus epidemic, the risk of GBS in Zika virus-infected persons, and the clinical management of GBS cases. We compared our estimates with those from the 2013-2014 Zika virus epidemic in French Polynesia. We were able to predict just a few weeks into the epidemic that, due to lower transmission potential and lower probability of developing GBS following infection in Martinique, the total number of GBS cases in Martinique would be substantially lower than suggested by simple extrapolations from French Polynesia. We correctly predicted that 8 intensive-care beds and 7 ventilators would be sufficient to treat GBS cases. This study showcased the contribution of modeling to inform local health-care planning during an outbreak. Timely studies that estimate the proportion of infected persons that seek care are needed to improve the predictive power of such approaches.

Keywords: Guillain-Barré syndrome; Zika virus; epidemic forecasts; health-care planning.

Figure 1.

Epidemic curves and model fit for French Polynesia, 2013–2014. A) Weekly number of consultations for suspected Zika virus (ZIKV) infection. B) Weekly number of Guillain-Barré syndrome (GBS) cases by hospitalization date. C) Weekly number of GBS cases in the intensive care unit (ICU). D) Weekly number of mechanically ventilated GBS cases. Triangles denote the data. Shaded area: 95% credible intervals.

Figure 2.

Epidemic curves and model fit for Martinique, France, as of week 32 in 2016. A) Weekly number of consultations for suspected Zika virus (ZIKV) infection. B) Weekly number of Guillain-Barré syndrome (GBS) cases by hospitalization date. C) Weekly number of GBS cases in the intensive care unit (ICU). D) Weekly number of mechanically ventilated GBS cases. Triangles denote the data; grey triangles in panel A indicate data points—not used for model fitting—with large uncertainties due to holidays. Shaded area: 95% credible intervals.

Figure 3.

Real-time estimates of key model parameters for Martinique, France, 2015–2016. A) Reproduction number R₀. B) Probability of seeking care for individuals infected with Zika virus. Solid and dashed lines in panels A and B denote the posterior means and 95% credible intervals obtained for French Polynesia. C) Risk ratio for Guillain-Barré syndrome in Martinique relative to French Polynesia. Dots and bars denote the posterior means and 95% credible intervals obtained for Martinique.

Figure 4.

Real-time estimates of the resources needed to manage Guillain-Barré syndrome (GBS) cases in Martinique, France, 2015–2016. A) Cumulative number of GBS cases. The dashed line corresponds to the total number of hospitalized GBS cases in Martinique as of week 32 in 2016 (26 cases). B) Required number of intensive care unit (ICU) beds. C) Required number of ventilators. Dots and bars denote the posterior means and 95% credible intervals.

Figure 5.

Seroprevalence of Zika virus in Martinique, France, 2016. The 2 stars represent independent seroprevalence estimates in blood donors (30). The black line and shaded area represent means and 95% credible intervals obtained from our model.