The West Africa Ebola outbreak of 2014-2016 demonstrated the importance of strong disease surveillance systems and the severe consequences of weak capacity to detect and respond to cases quickly. Challenges in the transmission and management of surveillance data were one factor that contributed to the delay in detecting and confirming the Ebola outbreak. To help address this challenge, we have collaborated with the U.S.

Dogs, cats and other companion animals have played an integral role in many aspects of human life. Human and companion animal (CAs) interactions have a wide range of benefits to human health [1-3]. The threat of zoonotic transmission between CAs and humans is exacerbated by proximity (56% of dog owners and 62% of cat owners sleep with their animal next to them [4]) and the number of diseases CAs share with humans. Many of these highlighted zoonoses are spread by direct contact, and others are vector-transmitted (e.g., fleas, ticks, flies, and mosquitos).

Hypertension (HTN) is a highly prevalent chronic condition and strongly associated with morbidity and mortality. HTN is amenable to prevention and control through public and population health programs and policies. Therefore, public and population health programs require accurate, stable estimates of disease prevalence, and estimating HTN prevalence at the community-level is acutely important for timely detection, intervention, and effective evaluation. Current surveillance methods for HTN rely upon community-based surveys, such as the BRFSS.

The importance transmitting clinical information to public health for disease surveillance is well-documented. Conventional reporting processes require health care providers to complete paper-based notifiable condition reports which are transmitted by fax and mail to public health agencies. These processes result in incomplete reports, inconsistencies in reporting frequencies among different diseases and reporting delays as well as time-consuming follow-up by public health to get needed information.