Introduction: Among the lessons learned from the 2009 influenza pandemic was the lack of a robust, standardized method that would allow a timely assessment of the severity of pandemic influenza. To remedy this deficiency, WHO has set up an evaluation tool based on the following indicators: 1) transmissibility, 2) seriousness of disease, and 3) impact of the influenza pandemic. By using this pandemic influenza severity assessment (PISA) tool, this study aimed to evaluate the severity of DRC influenza seasons between 2015 and 2019 to better prepare the country against the possible occurrence of an influenza pandemic. Methods: We performed a secondary data analysis from the DRC Influenza routine surveillance. We only explored the transmissibility among PISA indicators. Results: The results of our study showed that the DRC influenza seasons had two waves. The first went from the 40th week to the 10th week, with a peak at the 50th week, and the second wave ran from the 15th week to the 40th, with a peak at the 19th week. There was an inter-wave period between the 10th and 15th weeks. Of all the studied seasons, 42.8% were characterized by low intensity, 33.3% by moderate intensity, 19.0% by high intensity, and 4.8% by extraordinary intensity. Conclusion: The use of the PISA transmissibility indicator has contributed to better understanding influenza seasons in the Democratic Republic of Congo.



Muhemedi, S. , Lusamba, P. , Changachanga, J. , Lubula, L. , Nkwembe, E. and Babakazo, P. (2022) The Application of Indicators to Assess the Severity of Seasonal Influenza Epidemics in Democratic Republic of Congo, 2015 to 2019. Open Journal of Respiratory Diseases, 12, 1-14. doi: 10.4236/ojrd.2022.121001.

Le lun. 10 janv. 2022 à 13:39, Eric Mafuta <ericmafuta2@gmail.com> a écrit :

Effect of resuscitation training and implementation of continuous electronic heart rate monitoring on identification of stillbirth



To evaluate the effect of resuscitation training and continuous electronic heart rate (HR) monitoring of non-breathing newborns on identification of stillbirth.


We conducted a pre-post interventional trial in three health facilities in the Democratic Republic of the Congo. We collected data on a retrospective control group of newborns that reflected usual resuscitation practice (Epoch 1). In the prospective, interventional group, skilled birth attendants received resuscitation training in Helping Babies Breathe and implemented continuous electronic HR monitoring of non-breathing newborns (Epoch 2). Our primary outcome was the incidence of stillbirth with secondary outcomes of fresh or macerated stillbirth, neonatal death before discharge and perinatal death. Among a subset, we conducted expert review of electronic HR data to estimate misclassification of stillbirth in Epoch 2. We used a generalized estimating equation, adjusted for variation within-facility, to compare risks between EPOCHs.


There was no change in total stillbirths following resuscitation training and continuous electronic HR monitoring of non-breathing newborns (aRR 1.15 [0.95, 1.39]). We observed an increased rate of macerated stillbirth (aRR 1.58 [1.24, 2.02]), death before discharge (aRR 3.31 [2.41, 4.54]), and perinatal death (aRR 1.61 [1.38, 1.89]) during the intervention period. In expert review, 20% of newborns with electronic HR data that were classified by SBAs as stillborn were liveborn.


Resuscitation training and use of continuous electronic HR monitoring did not reduce stillbirths nor eliminate misclassification.