The Invisible Burden: Diagnosing and Combatting Typhoid Fever in Asia and Africa.

Measuring the burden of typhoid fever and developing effective strategies to reduce it require a surveillance infrastructure that is currently lacking in many endemic countries. Recent efforts and partnerships between local and international researchers have helped to provide new data on the incidence and control of typhoid in parts of Asia and Africa. Here, we highlight examples from India, Nepal, Vietnam, Fiji, Sierra Leone, and Malawi that summarize past and present experiences with the diagnosis, treatment, and prevention of typhoid fever in different locations with endemic disease. While there is no validated road map for the elimination of typhoid, the lessons learned in studying the epidemiology and control of typhoid in these settings can provide insights to guide future disease control efforts.

Frequency and spelling of names in the Sierra Leone Ebola Database.

Although there is no published analysis of surnames and given names used in Sierra Leone, certain names are common and identical names are frequently encountered. This makes disease tracking and contact tracing difficult. During the Ebola outbreak in 2014-2016, deficiencies in public health information systems in Sierra Leone exacerbated data collection difficulties. The study objective was to examine frequency of names recorded in the Viral Hemorrhagic Fever database (VHF) component of the Sierra Leone Ebola Database (SLED). First names and surnames were standardized by a Sierra Leonean linguist. Frequencies of standardized first names, surnames, full names, and initials were analyzed. The most frequent surname was used by 18.2% of VHF records and the most frequent 20 surnames accounted for 74.1%. The most frequent male first name accounted for 5.5% of VHF records and the most frequent female first name for 4.6%. The 20 most frequent full names accounted for 12.4% of records, and the most frequent initials were used in 7.3% of VHF records. A limited number of names are used in Sierra Leone, which poses a challenge to large public health responses. Algorithms that address inconsistent spelling could be used to improve computer-based databases. Databases must also use variables other than name for identification. The lessons learned in this analysis can assist other investigations, particularly those requiring contact tracing to limit disease spread.

Interruption of tuberculosis detection and care during the Ebola virus disease epidemic (2014-2015) in Liberia: time-series analyses for 2013-2017.

OBJECTIVE: Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014-2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia. METHODS: A segmented linear regression model was used to generate estimates and predictions for trends for three TB service indicators before, during, and after EVD, from January 2013 to December 2017. RESULTS: It was found that the number of presumptive TB cases declined significantly at the start of the EVD outbreak, with an estimated loss of 3222 cases (95% confidence interval (CI) -5691 to -752; P = 0.014). There was also an estimated loss of 709 cases per quarter post-EVD (95% CI -1346 to -71; P = 0.032). However, over the post-EVD period, quarterly increases were observed in the proportion of smear-positive to presumptive cases (1.45%, 95% CI 0.38% to 2.5%; P = 0.011) and the proportion of treatment success to TB cases evaluated (3.3%, 95% CI 0.82% to 5.79%; P = 0.013). CONCLUSIONS: These findings suggest that the EVD outbreak (2014-2015) negatively affected TB care services. Rigorous quantitative analyses can be used to assess the magnitude of interruption and advocate for preparedness in settings with limited healthcare capacity.

Quality of age data in the Sierra Leone Ebola database.

INTRODUCTION: While it is suspected that some ages were misreported during the 2014-2016 West African Ebola outbreak, an analysis examining age data quality has not been conducted. The study objective was to examine age heaping and terminal digit preference as indicators for quality of age data collected in the Sierra Leone Ebola Database (SLED). METHODS: Age data quality for adult patients was analyzed within SLED for the Viral Hemorrhagic Fever (VHF) database and the laboratory testing dataset by calculating Whipple´s index and Myers´s blended index, stratified by sex and region. RESULTS: Age data quality was low in both the VHF database (Whipple´s index for the 5-year range, 229.2) and the laboratory testing dataset (Whipple´s index for the 5-year range, 236.4). Age was reported more accurately in the Western Area and least accurately in the Eastern Province. Age data for females were less accurate than for males. CONCLUSION: Age data quality was low in adult patients during the 2014-2016 Ebola outbreak in Sierra Leone, which may reduce its use as an identifying or stratifying variable. These findings inform future analyses using this database and describe a phenomenon that has relevance in data collection methods and analyses for future outbreaks in developing countries.

Towards an understanding of resilience: responding to health systems shocks.

The recent outbreak of Ebola Virus Disease (EVD) in West Africa has drawn attention to the role and responsiveness of health systems in the face of shock. It brought into sharp focus the idea that health systems need not only to be stronger but also more 'resilient'. In this article, we argue that responding to shocks is an important aspect of resilience, examining the health system behaviour in the face of four types of contemporary shocks: the financial crisis in Europe from 2008 onwards; climate change disasters; the EVD outbreak in West Africa 2013-16; and the recent refugee and migration crisis in Europe. Based on this analysis, we identify '3 plus 2' critical dimensions of particular relevance to health systems' ability to adapt and respond to shocks; actions in all of these will determine the extent to which a response is successful. These are three core dimensions corresponding to three health systems functions: 'health information systems' (having the information and the knowledge to make a decision on what needs to be done); 'funding/financing mechanisms' (investing or mobilising resources to fund a response); and 'health workforce' (who should plan and implement it and how). These intersect with two cross-cutting aspects: 'governance', as a fundamental function affecting all other system dimensions; and predominant 'values' shaping the response, and how it is experienced at individual and community levels. Moreover, across the crises examined here, integration within the health system contributed to resilience, as does connecting with local communities, evidenced by successful community responses to Ebola and social movements responding to the financial crisis. In all crises, inequalities grew, yet our evidence also highlights that the impact of shocks is amenable to government action. All these factors are shaped by context. We argue that the '3 plus 2' dimensions can inform pragmatic policies seeking to increase health systems resilience.