Lessons Learned From a Large Cross-Border Field Simulation Exercise to Strengthen Emergency Preparedness in East Africa, 2019

Field simulation exercises (FSXs) require substantial time, resources, and organizational experience to plan and implement and are less commonly undertaken than drills or tabletop exercises. Despite this, FSXs provide an opportunity to test the full scope of operational capacities, including coordination across sectors. From June 11 to 14, 2019, the East African Community Secretariat conducted a cross-border FSX at the Namanga One Stop Border Post between the Republic of Kenya and the United Republic of Tanzania. The World Health Organization Department of Health Security Preparedness was the technical lead responsible for developing and coordinating the exercise. The purpose of the FSX was to assess and further enhance multisectoral outbreak preparedness and response in the East Africa Region, using a One Health approach. Participants included staff from the transport, police and customs, public health, animal health, and food inspection sectors. This was the first FSX of this scale, magnitude, and complexity to be conducted in East Africa for the purpose of strengthening emergency preparedness capacities. The FSX provided an opportunity for individual learning and national capacity strengthening in emergency management and response coordination. In this article, we describe lessons learned and propose recommendations relevant to FSX design, management, and organization to inform future field exercises.

Unexpected Rift Valley fever outbreak, northern Mauritania

During September-October 2010, an unprecedented outbreak of Rift Valley fever was reported in the northern Sahelian region of Mauritania after exceptionally heavy rainfall. Camels probably played a central role in the local amplification of the virus. We describe the main clinical signs (hemorrhagic fever, icterus, and nervous symptoms) observed during the outbreak.

Comparing national and global data collection systems for reporting, outbreaks of H5N1 HPAI

Determining if outbreak data collected by regional or international organizations can reflect patterns observed in more detailed data collected by national veterinary services is a necessary first step if global databases are to be used for making inference about determinants of disease maintenance and spread and for emergency planning and response. We compared two data sources that capture spatial and temporal information about H5N1 highly pathogenic avian influenza outbreaks reported since 2004 in four countries: Bangladesh, Egypt, Turkey, and Vietnam. One data source consisted of reports collected as part of each country's national veterinary services surveillance program, while the other data source included reports collected using the Emergency Prevention System for Priority Animal and Plant Pests and Diseases (EMPRES-i) global animal health information system. We computed Spearman rank-order correlation statistics to compare spatial and temporal outbreak distributions, and applied a space-time permutation test to check for consistency between the two data sources. Although EMPRES-i typically captured fewer outbreaks than detailed national reporting data, the overall similarity in space and time, particularly after 2006, reflect the ability of the EMPRES-i system to portray disease patterns comparable to those observed in national data sets. Specifically, we show that the two datasets exhibit higher positive correlations in outbreak timing and reported locations after 2006 when compared to December 2003 through 2006. Strengthening the capacity of global systems to acquire data from national and regional databases will improve global analysis efforts and increase the ability of such systems to rapidly alert countries and the international community of potential disease threats.

Prediction, assessment of the Rift Valley fever activity in East and Southern Africa 2006-2008 and possible vector control strategies

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Niño/Southern Oscillation (ENSO) phenomenon, which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and regional elevated sea surface temperatures, elevated rainfall, and satellite derived-normalized difference vegetation index data, we predicted with lead times of 2-4 months areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa, Sudan, and Southern Africa at different time periods from September 2006 to March 2008. Predictions were confirmed by entomological field investigations of virus activity and by reported cases of RVF in human and livestock populations. This represents the first series of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation into the future.