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Large-scale protracted outbreaks can be prevented through early detection, notification, and rapid control. We assessed trends in timeliness of detecting and responding to outbreaks in the African Region reported to the World Health Organization during 2017-2019. We computed the median time to each outbreak milestone and assessed the rates of change over time using univariable and multivariable Cox proportional hazard regression analyses. We selected 296 outbreaks from 348 public reported health events and evaluated 184 for time to detection, 232 for time to notification, and 201 for time to end. Time to detection and end decreased over time, whereas time to notification increased. Multiple factors can account for these findings, including scaling up support to member states after the World Health Organization established its Health Emergencies Programme and support given to countries from donors and partners to strengthen their core capacities for meeting International Health Regulations.

A group convened and led by the Virus Evolution Working Group of the World Health Organization reports on its deliberations and announces a naming scheme that will enable clear communication about SARS-CoV-2 variants of interest and concern.

The end-of-outbreak declaration is an important step in controlling infectious disease outbreaks. Objective estimation of the confidence level that an outbreak is over is important to reduce the risk of postdeclaration flare-ups. We developed a simulation-based model with which to quantify that confidence and tested it on simulated Ebola virus disease data. We found that these confidence estimates were most sensitive to the instantaneous reproduction number, the reporting rate, and the time between the symptom onset and death or recovery of the last detected case. For Ebola virus disease, our results suggested that the current World Health Organization criterion of 42 days since the recovery or death of the last detected case is too short and too sensitive to underreporting. Therefore, we suggest a shift to a preliminary end-of-outbreak declaration after 63 days from the symptom onset day of the last detected case. This preliminary declaration should still be followed by 90 days of enhanced surveillance to capture potential flare-ups of cases, after which the official end of the outbreak can be declared. This sequence corresponds to more than 95% confidence that an outbreak is over in most of the scenarios examined. Our framework is generic and therefore could be adapted to estimate end-of-outbreak confidence for other infectious diseases.

Ebola virus (EBOV) can persist in immunologically protected body sites in survivors of Ebola virus disease, creating the potential to initiate new chains of transmission. From the outbreak in West Africa during 2014-2016, we identified 13 possible events of viral persistence-derived transmission of EBOV (VPDTe) and applied predefined criteria to classify transmission events based on the strength of evidence for VPDTe and source and route of transmission. For 8 events, a recipient case was identified; possible source cases were identified for 5 of these 8. For 5 events, a recipient case or chain of transmission could not be confidently determined. Five events met our criteria for sexual transmission (male-to-female). One VPDTe event led to at least 4 generations of cases; transmission was limited after the other events. VPDTe has increased the importance of Ebola survivor services and sustained surveillance and response capacity in regions with previously widespread transmission.

Background The WHO African region frequently experiences outbreaks and epidemics of infectious diseases often exacerbated by weak health systems and infrastructure, late detection, and ineffective outbreak response. To address this, the WHO Regional Office for Africa developed and began implementing the Integrated Disease Surveillance and Response strategy in 1998. Objectives This systematic review aims to document the identified successes and challenges surrounding the implementation of IDSR in the region available in published literature to highlight areas for prioritization, further research, and to inform further strengthening of IDSR implementation. Methods A systematic review of peer-reviewed literature published in English and French from 1 July 2012 to 13 November 2019 was conducted using PubMed and Web of Science. Included articles focused on the WHO African region and discussed the use of IDSR strategies and implementation, assessment of IDSR strategies, or surveillance of diseases covered in the IDSR framework. Data were analyzed descriptively using Microsoft Excel and Tableau Desktop 2019. Results The number of peer-reviewed articles discussing IDSR remained low, with 47 included articles focused on 17 countries and regional level systems. Most commonly discussed topics were data reporting (n = 39) and challenges with IDSR implementation (n = 38). Barriers to effective implementation were identified across all IDSR core and support functions assessed in this review: priority disease detection; data reporting, management, and analysis; information dissemination; laboratory functionality; and staff training. Successful implementation was noted where existing surveillance systems and infrastructure were utilized and streamlined with efforts to increase access to healthcare. Conclusions and implications of findings These findings highlighted areas where IDSR is performing well and where implementation remains weak. While challenges related to IDSR implementation since the first edition of the technical guidelines were released are not novel, adequately addressing them requires sustained investments in stronger national public health capabilities, infrastructure, and surveillance processes.

Background The COVID-19 pandemic has created unprecedented challenges to the systematic and timely sharing of COVID-19 field data collection and management. The World Health Organization (WHO) is working with health partners on the rollout and implementation of a robust electronic field data collection platform. The delay in the deployment and rollout of this electronic platform in the WHO African Region, as a consequence of the application of large-scale public health and social measures including movement restrictions and geographical area quarantine, left a gap between data collection and management. This lead to the need to develop interim data management solutions to accurately monitor the evolution of the pandemic and support the deployment of appropriate public health interventions. Objective The aim of this study is to review the design, development, and implementation of the COVID-19 Data Summarization and Visualization (DSV) tool as a rapidly deployable solution to fill this critical data collection gap as an interim solution. Methods This paper reviews the processes undertaken to research and develop a tool to bridge the data collection gap between the onset of a COVID-19 outbreak and the start of data collection using a prioritized electronic platform such as Go.Data in the WHO African Region. Results In anticipation of the implementation of a prioritized tool for field data collection, the DSV tool was deployed in 18 member states for COVID-19 outbreak data management. We highlight preliminary findings and lessons learned from the DSV tool deployment in the WHO African Region. Conclusions We developed a rapidly deployable tool for COVID-19 data collection and visualization in the WHO African Region. The lessons drawn on this experience offer an opportunity to learn and apply these to improve future similar public health informatics initiatives in an outbreak or similar humanitarian setting, particularly in low- and middle-income countries.

Background Typhoid fever, caused by S. enterica ser. Typhi, continues to be a substantial health burden in developing countries. Little is known of the genotypic diversity of S. enterica ser. Typhi in Zimbabwe, but this is key for understanding the emergence and spread of this pathogen and devising interventions for its control. Objectives To report the molecular epidemiology of S. enterica ser. Typhi outbreak strains circulating from 2012 to 2019 in Zimbabwe, using comparative genomics. Methods A review of typhoid cases records from 2012 to 2019 in Zimbabwe was performed. The phylogenetic relationship of outbreak isolates from 2012 to 2019 and emergence of antibiotic resistance was investigated by whole-genome sequence analysis. Results A total 22 479 suspected typhoid cases, 760 confirmed cases were reported from 2012 to 2019 and 29 isolates were sequenced. The majority of the sequenced isolates were predicted to confer resistance to aminoglycosides, β-lactams, phenicols, sulphonamides, tetracycline and fluoroquinolones (including qnrS detection). The qnrS1 gene was associated with an IncN (subtype PST3) plasmid in 79% of the isolates. Whole-genome SNP analysis, SNP-based haplotyping and resistance determinant analysis showed that 93% of the isolates belonged to a single clade represented by multidrug-resistant H58 lineage I (4.3.1.1), with a maximum pair-wise distance of 22 SNPs. Conclusions This study has provided detailed genotypic characterization of the outbreak strain, identified as S. Typhi 4.3.1.1 (H58). The strain has reduced susceptibility to ciprofloxacin due to qnrS carried by an IncN (subtype PST3) plasmid resulting from ongoing evolution to full resistance.

BACKGROUND The COVID-19 pandemic has created unprecedented challenges to the systematic and timely sharing of COVID-19 field data collection and management. The World Health Organization (WHO) is working with health partners on the rollout and implementation of a robust electronic field data collection platform. The delay in the deployment and rollout of this electronic platform in the WHO African Region, as a consequence of the application of large-scale public health and social measures including movement restrictions and geographical area quarantine, left a gap between data collection and management. This lead to the need to develop interim data management solutions to accurately monitor the evolution of the pandemic and support the deployment of appropriate public health interventions. OBJECTIVE The aim of this study is to review the design, development, and implementation of the COVID-19 Data Summarization and Visualization (DSV) tool as a rapidly deployable solution to fill this critical data collection gap as an interim solution. METHODS This paper reviews the processes undertaken to research and develop a tool to bridge the data collection gap between the onset of a COVID-19 outbreak and the start of data collection using a prioritized electronic platform such as Go.Data in the WHO African Region. RESULTS In anticipation of the implementation of a prioritized tool for field data collection, the DSV tool was deployed in 18 member states for COVID-19 outbreak data management. We highlight preliminary findings and lessons learned from the DSV tool deployment in the WHO African Region. CONCLUSIONS We developed a rapidly deployable tool for COVID-19 data collection and visualization in the WHO African Region. The lessons drawn on this experience offer an opportunity to learn and apply these to improve future similar public health informatics initiatives in an outbreak or similar humanitarian setting, particularly in low- and middle-income countries.

Declaring the end of an outbreak is an important step in controlling infectious disease outbreaks. An objective estimation of the probability of cases arising in the future is important to reduce the risk of post-declaration flare-ups. We developed a simulation-based model to quantify that probability. We tested it on simulated Ebola Virus Disease (EVD) data and found this probability was most sensitive to the instantaneous reproduction number, the reporting rate, and the delay between symptom onset and recovery or death of the last detected case. For EVD, our results suggest that the current WHO criterion of 42 days since the outcome of the last detected case is too short and very sensitive to underreporting. The 90 days of enhanced surveillance period after the end-of-outbreak declaration is therefore crucial to capture potential flare-ups of cases. Hence, we suggest a shift to a preliminary end-of-outbreak declaration after 63 days from the symptom onset day of the last detected case. This should be followed by a 90-day enhanced surveillance, after which the official end-of-outbreak can be declared. This corresponds to less than 5% probability of flare ups in most of the scenarios examined. Our quantitative framework could be adapted to define end-of-outbreak criteria for other infectious diseases.

Objective During the 2017–2018 cholera outbreak in Kinshasa, many patients initially reported to primary healthcare centers (HCs) before being transferred to the nearest cholera treatment centers. This study aims to assess the level of preparedness of HCs in responding to cholera outbreaks. Study design Descriptive cross-sectional survey. Methods We conducted a descriptive cross-sectional survey in 180 of 374 primary HCs in Kinshasa. We collected data on 14 cholera preparedness criteria and described their prevalence among HCs. We used logistic regression to assess the association between each preparedness criteria and previous reporting of cholera cases by HCs. Results The median number of preparedness criteria met by HCs was 5 [range: 0–11]. Five percent (n = 9) of HCs [95% confidence interval (CI): 2.3%–9.3%] met at least 10 criteria. HCs that previously reported ≥3 cholera cases were less likely to meet the criteria for ‘presence of an isolation unit’ (adjusted odds ratio [aOR]: 0.12; 95% CI [0.03–0.61]) and ‘availability of sufficient quantity of chlorine’ (aOR: 0.13; 95% CI [0.02–0.64]). Conclusions Despite past experience of cholera cases, health facilities in Kinshasa exhibit a low level of cholera preparedness. There is a need to prioritize the reinforcement of the preparedness of primary HCs to prevent future cholera outbreaks.

Objectives Lassa fever (LF), a priority emerging pathogen likely to cause major epidemics, is endemic in much of West Africa and is difficult to distinguish from other viral hemorrhagic fevers, including Ebola virus disease (EVD). Definitive diagnosis requires laboratory confirmation, which is not widely available in affected settings. The public health action to contain a LF outbreak and the challenges encountered in an EVD-affected setting are reported herein. Methods In February 2016, a rapid response team was deployed in Liberia in response to a cluster of LF cases. Active case finding, case investigation, contact tracing, laboratory testing, environmental investigation, risk communication, and community awareness raising were undertaken. Results From January to June 2016, 53 suspected LF cases were reported through the Integrated Disease Surveillance and Response system (IDSR). Fourteen cases (26%) were confirmed for LF, 14 (26%) did not have a sample tested, and 25 (47%) were classified as not a case following laboratory analysis. The case fatality rate in the confirmed cases was 29%. One case of international exportation was reported from Sweden. Difficulties were identified in timely specimen collection, packaging, and transportation (in confirmed cases, the time from sample collection to sample result ranged from 2 to 64 days) and a lack of response interventions for early cases. Conclusions The delay in response to this outbreak could have been related to a number of challenges in this EVD-affected setting: a need to strengthen the IDSR system, develop preparedness plans, train rapid response teams, and build laboratory capacity. Prioritizing these actions will aid in the timely response to future outbreaks.

Introduction in spite of the efforts and resources committed by the division of infectious disease and epidemiology (DIDE) of the national public health institute of Liberia (NPHIL)/Ministry of health to strengthening integrated disease surveillance and response (IDSR) across the country, quality data management system remains a challenge to the Liberia NPHIL/MoH (Ministry of health), with incomplete and inconsistent data constantly being reported at different levels of the surveillance system. As part of the monitoring and evaluation strategy for IDSR continuous improvement, data quality assessment (DQA) of the IDSR system to identify successes and gaps in the disease surveillance information system (DSIS) with the aim of ensuring data accuracy, reliability and credibility of generated data at all levels of the health system; and to inform an operational plan to address data quality needs for IDSR activities is required. Methods multi-stage cluster sampling that included stage 1: simple random sample (SRS) of five counties, stage 2: simple random sample of two districts and stage 3: simple random sample of three health facilities was employed during the study pilot assessment done in Montserrado County with Liberia institute of bio medical research (LIBR) inclusive. A total of thirty (30) facilities was targeted, twenty nine (29) of the facilities were successfully audited: one hospital, two health centers, twenty clinics and respondents included: health facility surveillance focal persons (HFSFP), zonal surveillance officers (ZSOs), district surveillance officers (DSOs) and County surveillance officers (CSOs). Results the assessment revealed that data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the subnational level. The findings indicated the following: 23% (7/29) of health facilities having dedicated phone for reporting, 20% (6/29) reported no cell phone network, 17% (5/29) reported daily access to internet, 56.6% (17/29) reported a consistent supply of electricity, and no facility reported access to functional laptop. It was also established that 40% of health facilities have experienced a stock out of laboratory specimens packaging supplies in the past year. About half of the surveyed health facilities delivered specimens through riders and were assisted by the DSOs. There was a large variety in the reported packaging process, with many staff unable to give clear processes. The findings during the exercise also indicated that 91% of health facility staff were mentored on data quality check and data management including the importance of the timeliness and completeness of reporting through supportive supervision and mentorship; 65% of the health facility assessed received supervision on IDSR core performance indicator; and 58% of the health facility officer in charge gave feedback to the community level. Conclusion public health is a data-intensive field which needs high-quality data and authoritative information to support public health assessment, decision-making and to assure the health of communities. Data quality assessment is important for public health. In this review completeness, accuracy, and timeliness were the three most-assessed attributes. Quantitative data quality assessment primarily used descriptive surveys and data audits, while qualitative data quality assessment methods include primarily interviews, questionnaires administration, documentation reviews and field observations. We found that data-use and data-process have not been given adequate attention, although they were equally important factors which determine the quality of data. Other limitations of the previous studies were inconsistency in the definition of the attributes of data quality, failure to address data users' concerns and a lack of triangulation of mixed methods for data quality assessment. The reliability and validity of the data quality assessment were rarely reported. These gaps suggest that in the future, data quality assessment for public health needs to consider equally the three dimensions of data quality, data use and data process. Measuring the perceptions of end users or consumers towards data quality will enrich our understanding of data quality issues. Data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the sub national level.

The WHO African region is characterised by the largest infectious disease burden in the world. We conducted a retrospective descriptive analysis using records of all infectious disease outbreaks formally reported to the WHO in 2018 by Member States of the African region. We analysed the spatio-temporal distribution, the notification delay as well as the morbidity and mortality associated with these outbreaks. In 2018, 96 new disease outbreaks were reported across 36 of the 47 Member States. The most commonly reported disease outbreak was cholera which accounted for 20.8% (n = 20) of all events, followed by measles (n = 11, 11.5%) and Yellow fever (n = 7, 7.3%). About a quarter of the outbreaks (n = 23) were reported following signals detected through media monitoring conducted at the WHO regional office for Africa. The median delay between the disease onset and WHO notification was 16 days (range: 0–184). A total of 107 167 people were directly affected including 1221 deaths (mean case fatality ratio (CFR): 1.14% (95% confidence interval (CI) 1.07%–1.20%)). The highest CFR was observed for diseases targeted for eradication or elimination: 3.45% (95% CI 0.89%–10.45%). The African region remains prone to outbreaks of infectious diseases. It is therefore critical that Member States improve their capacities to rapidly detect, report and respond to public health events.

Introduction Measles is an acute viral disease that remains endemic in much of sub-Sahara Africa, including Liberia. The 2014 Ebola epidemic disrupted an already fragile health system contributing to low uptake of immunization services, population immunity remained low thus facilitating recurrent outbreaks of measles in Liberia. We describe lessons learnt from detecting and responding to recurrent outbreaks of measles two years post the 2014 Ebola epidemic in Liberia. Methods We conducted a descriptive study using the findings from Integrated Diseases Surveillance and Response (IDSR) 15 counties, National Public Health Institute of Liberia (NPHIL), National Public Health Reference Laboratory (NPHRL) and District Health Information Software (DIHS2) data conducted from October to December, 2017. We perused the outbreaks line lists and other key documents submitted by the counties to the national level from January 2016 to December 2017. Results From January 2016 to December 2017, 2,954 suspected cases of measles were reported through IDSR. Four hundred sixty-seven (467) were laboratory confirmed (IgM-positive), 776 epidemiologically linked, 574 clinically confirmed, and 1,137 discarded (IgM-negative). Nine deaths out of 1817 cases were reported, a case fatality rate of 0.5%; 49% were children below the age of 5 years. Twenty-two percent (405/1817) of the confirmed cases were vaccinated while the vaccination status of 55% (994/1817) was unknown. Conclusion Revitalization of IDSR contributed to increased detection and reporting of suspected cases of measles thus facilitating early identification and response to outbreaks. Priority needs to be given to increasing the uptake of routine immunization services, introducing a second dose of measles vaccine in the routine immunization program and conducting a high-quality supplementary measles immunization campaign for age group 1 to 10 years to provide protection for a huge cohort of susceptible.

Background The incidence of TB has doubled in the last 20 years in London. A better understanding of risk groups for recent transmission is required to effectively target interventions. We investigated the molecular epidemiological characteristics of TB cases to estimate the proportion of cases due to recent transmission, and identify predictors for belonging to a cluster. Methods The study population included all culture-positive TB cases in London residents, notified between January 2010 and December 2012, strain typed using 24-loci multiple interspersed repetitive units-variable number tandem repeats. Multivariable logistic regression analysis was performed to assess the risk factors for clustering using sociodemographic and clinical characteristics of cases and for cluster size based on the characteristics of the first two cases. Results There were 10 147 cases of which 5728 (57%) were culture confirmed and 4790 isolates (84%) were typed. 2194 (46%) were clustered in 570 clusters, and the estimated proportion attributable to recent transmission was 34%. Clustered cases were more likely to be UK born, have pulmonary TB, a previous diagnosis, a history of substance abuse or alcohol abuse and imprisonment, be of white, Indian, black-African or Caribbean ethnicity. The time between notification of the first two cases was more likely to be

The 2017 plague outbreak in Madagascar was unprecedented in the African region, resulting in 2417 cases (498 confirmed, 793 probable and 1126 suspected) and 209 deaths by the end of the acute urban pneumonic phase of the outbreak. The Health Emergencies Programme of the WHO Regional Office for Africa together with the WHO Country Office and WHO Headquarters assisted the Ministry of Public Health of Madagascar in the rapid implementation of plague prevention and control measures while collecting and analysing quantitative and qualitative data to inform immediate interventions. We document the key findings of the evidence available to date and actions taken as a result. Based on the four goals of operational research – effective dissemination of results, peer-reviewed publication, changes to policy and practice and improvements in programme performance and health – we evaluate the use of evidence to inform response to the outbreak and describe lessons learned for future outbreak responses in the WHO African region. This article may not be reprinted or reused in any way in order to promote any commercial products or services.

Background\ud \ud On May 8, 2018, the Government of the Democratic Republic of the Congo reported an outbreak of Ebola virus disease in Équateur Province in the northwest of the country. The remoteness of most affected communities and the involvement of an urban centre connected to the capital city and neighbouring countries makes this outbreak the most complex and high risk ever experienced by the Democratic Republic of the Congo. We provide early epidemiological information arising from the ongoing investigation of this outbreak.\ud Methods\ud \ud We classified cases as suspected, probable, or confirmed using national case definitions of the Democratic Republic of the Congo Ministère de la Santé Publique. We investigated all cases to obtain demographic characteristics, determine possible exposures, describe signs and symptoms, and identify contacts to be followed up for 21 days. We also estimated the reproduction number and projected number of cases for the 4-week period from May 25, to June 21, 2018.\ud Findings\ud \ud As of May 30, 2018, 50 cases (37 confirmed, 13 probable) of Zaire ebolavirus were reported in the Democratic Republic of the Congo. 21 (42%) were reported in Bikoro, 25 (50%) in Iboko, and four (8%) in Wangata health zones. Wangata is part of Mbandaka, the urban capital of Équateur Province, which is connected to major national and international transport routes. By May 30, 2018, 25 deaths from Ebola virus disease had been reported, with a case fatality ratio of 56% (95% CI 39–72) after adjustment for censoring. This case fatality ratio is consistent with estimates for the 2014–16 west African Ebola virus disease epidemic (p=0·427). The median age of people with confirmed or probable infection was 40 years (range 8–80) and 30 (60%) were male. The most commonly reported signs and symptoms in people with confirmed or probable Ebola virus disease were fever (40 [95%] of 42 cases), intense general fatigue (37 [90%] of 41 cases), and loss of appetite (37 [90%] of 41 cases). Gastrointestinal symptoms were frequently reported, and 14 (33%) of 43 people reported haemorrhagic signs. Time from illness onset and hospitalisation to sample testing decreased over time. By May 30, 2018, 1458 contacts had been identified, of which 746 (51%) remained under active follow-up. The estimated reproduction number was 1·03 (95% credible interval 0·83–1·37) and the cumulative case incidence for the outbreak by June 21, 2018, is projected to be 78 confirmed cases (37–281), assuming heterogeneous transmissibility.\ud Interpretation\ud \ud The ongoing Ebola virus outbreak in the Democratic Republic of the Congo has similar epidemiological features to previous Ebola virus disease outbreaks. Early detection, rapid patient isolation, contact tracing, and the ongoing vaccination programme should sufficiently control the outbreak. The forecast of the number of cases does not exceed the current capacity to respond if the epidemiological situation does not change. The information presented, although preliminary, has been essential in guiding the ongoing investigation and response to this outbreak.

Summary Background Outbreak response efforts for the 2014–15 Ebola virus disease epidemic in west Africa brought widespread transmission to an end. However, subsequent clusters of infection have occurred in the region. An Ebola virus disease cluster in Liberia in November, 2015, that was identified after a 15-year-old boy tested positive for Ebola virus infection in Monrovia, raised the possibility of transmission from a persistently infected individual. Methods Case investigations were done to ascertain previous contact with cases of Ebola virus disease or infection with Ebola virus. Molecular investigations on blood samples explored a potential linkage between Ebola virus isolated from cases in this November, 2015, cluster and epidemiologically linked cases from the 2014–15 west African outbreak, according to the national case database. Findings The cluster investigated was the family of the index case (mother, father, three siblings). Ebola virus genomes assembled from two cases in the November, 2015, cluster, and an epidemiologically linked Ebola virus disease case in July, 2014, were phylogenetically related within the LB5 sublineage that circulated in Liberia starting around August, 2014. Partial genomes from two additional individuals, one from each cluster, were also consistent with placement in the LB5 sublineage. Sequencing data indicate infection with a lineage of the virus from a former transmission chain in the country. Based on serology and epidemiological and genomic data, the most plausible scenario is that a female case in the November, 2015, cluster survived Ebola virus disease in 2014, had viral persistence or recurrent disease, and transmitted the virus to three family members a year later. Interpretation Investigation of the source of infection for the November, 2015, cluster provides evidence of Ebola virus persistence and highlights the risk for outbreaks after interruption of active transmission. These findings underscore the need for focused prevention efforts among survivors and sustained capacity to rapidly detect and respond to new Ebola virus disease cases to prevent recurrence of a widespread outbreak. Funding US Centers for Disease Control and Prevention, Defense Threat Reduction Agency, and WHO.

Objectives Tuberculosis (TB) is a serious re-emergent public health problem in the UK. In response to rising case incidence a National TB Strain-Typing Service based on molecular strain-typing was established. This facilitates early detection and investigation of clusters, targeted public health action, and prevention of further transmission. We review the added public health value of investigating molecular TB strain-typed (ST) clusters. Methods A structured questionnaire for each ST cluster investigated in England between 1 January 2010 and 30 June 2013 was completed. Questions related to epidemiological links and public health action and the perceived benefits of ST cluster investigation. Results There were 278 ST cluster investigations (CIs) involving 1882 TB cases. Cluster size ranged from 2 to 92. CIs identified new epidemiological links in 36% of clusters; in 18% STs were discordant refuting transmission thought to have occurred. Additional public health action was taken following 23% of CI. Conclusions We found positive benefits of TB molecular ST and CI, in identifying new epidemiological links between cases and taking public health action and in refuting transmission and saving resources. This needs to be translated to a decrease in transmission to provide evidence of public health value in this low prevalence high resource setting.

The 2014–16 Ebola Virus Disease (EVD) outbreak in West Africa highlighted the necessity for readily available, accurate and rapid diagnostics. The magnitude of the outbreak and the re-emergence of clusters of EVD cases following the declaration of interrupted transmission in Liberia, reinforced the need for sustained diagnostics to support surveillance and emergency preparedness. We describe implementation of the Xpert Ebola Assay, a rapid molecular diagnostic test run on the GeneXpert platform, at a mobile laboratory in Liberia and the subsequent impact on EVD outbreak response, case management and laboratory system strengthening. During the period of operation, site coordination, management and operational capacity was supported through a successful collaboration between Ministry of Health (MoH), World Health Organization (WHO) and international partners. A team of Liberian laboratory technicians were trained to conduct EVD diagnostics and the laboratory had capacity to test 64–100 blood specimens per day. Establishment of the laboratory significantly increased the daily testing capacity for EVD in Liberia, from 180 to 250 specimens at a time when the effectiveness of the surveillance system was threatened by insufficient diagnostic capacity. During the 18 months of operation, the laboratory tested a total of 9,063 blood specimens, including 21 EVD positives from six confirmed cases during two outbreaks. Following clearance of the significant backlog of untested EVD specimens in November 2015, a new cluster of EVD cases was detected at the laboratory. Collaboration between surveillance and laboratory coordination teams during this and a later outbreak in March 2016, facilitated timely and targeted response interventions. Specimens taken from cases during both outbreaks were analysed at the laboratory with results informing clinical management of patients and discharge decisions. The GeneXpert platform is easy to use, has relatively low running costs and can be integrated into other national diagnostic algorithms. The technology has on average a 2-hour sample-to-result time and allows for single specimen testing to overcome potential delays of batching. This model of a mobile laboratory equipped with Xpert Ebola test, staffed by local laboratory technicians, could serve to strengthen outbreak preparedness and response for future outbreaks of EVD in Liberia and the region., Author summary We describe a model of a mobile laboratory co-located at an Ebola treatment unit (ETU) equipped with GeneXpert molecular diagnostic platform and automated qRT-PCR test for Ebola virus disease (EVD). The laboratory contributed significantly to the EVD response in Liberia, including supporting surveillance, outbreak detection, contact tracing and management of confirmed cases. The laboratory was run by local laboratory technicians as opposed to international experts on short missions, making it a more sustainable option in prolonged outbreaks and early recovery phases. The redeployment and strategic placement of these GeneXpert instruments to complement EVD isolation facilities throughout the country has strengthened preparedness and response capabilities for future EVD outbreaks in Liberia.

Background We estimate the proportion of tuberculosis (TB) in England due to recent household transmission, identify factors associated with being a household transmitter, and investigate the impact that identification of a case has on time to treatment of subsequent cases. Methods TB cases notified between 2010 and 2012 in England in the same household as another case were identified; 24 locus MIRU-VNTR strain typing (ST) was used to identify household cases with likely recent transmission. Treatment delay in index and subsequent cases was compared. Risk factors for being a household transmitter were identified in univariable and multivariable analyses. Results Overall, 7.7% (1849/24,060) of TB cases lived in a household with another case. We estimate that 3.9% were due to recent household transmission. ST data was unavailable for 67% (1242) of household pairs. For those with ST data, 64% (386) had confirmed, 11% probable (66) and 25% (155) refuted household transmission. The median treatment delay was 65 days for index cases and 37 days for subsequent asymptomatic cases. Risk factors for being a household transmitter included being under 25 years old, UK-born with Black African, Indian or Pakistani ethnicity, or born in Somalia or Romania. Conclusions This study has a number of implications for household TB contact tracing in low incidence countries, including the potential to reduce the diagnostic delay for subsequent household cases and the benefit of using ST to identify when to conduct source contact tracing outside the household. As 25% of TB cases in households had discordant strains, households with multiple TB cases do not necessarily represent household transmission. The additional fact that 25% of index cases within households only had extra-pulmonary TB demonstrates that, if household contact tracing is limited to pulmonary TB cases (as recently recommended in UK guidelines), additional cases of active TB in households will be missed. Our finding that no lineage of TB was associated with recent household transmission and with no increased transmissibility in the Beijing lineage compared to others, suggests that the lineage need not impact contact tracing efforts. Improvements in contact tracing have the potential to reduce transmission of TB in low incidence countries. Electronic supplementary material The online version of this article (doi:10.1186/s12916-017-0864-y) contains supplementary material, which is available to authorized users.

Background Contact tracing is one of the key response activities necessary for halting Ebola Virus Disease (EVD) transmission. Key elements of contact tracing include identification of persons who have been in contact with confirmed EVD cases and careful monitoring for EVD symptoms, but the details of implementation likely influence their effectiveness. In November 2015, several months after a major Ebola outbreak was controlled in Liberia, three members of a family were confirmed positive for EVD in the Duport Road area of Monrovia. The cluster provided an opportunity to implement and evaluate modified approaches to contact tracing. Methods The approaches employed for improved contact tracing included classification and risk-based management of identified contacts (including facility based isolation of some high risk contacts, provision of support to persons being monitored, and school-based surveillance for some persons with potential exposure but not listed as contacts), use of phone records to help locate missing contacts, and modifications to data management tools. We recorded details about the implementation of these approaches, report the overall outcomes of the contact tracing efforts and the challenges encountered, and provide recommendations for management of future outbreaks. Results 165 contacts were identified (with over 150 identified within 48 hours of confirmation of the EVD cases) and all initially missing contacts were located. Contacts were closely monitored and promptly tested if symptomatic; no contacts developed disease. Encountered challenges related to knowledge gaps among contact tracing staff, data management, and coordination of contact tracing activities with efforts to offer Ebola vaccine. Conclusions The Duport Road EVD cluster was promptly controlled. Missing contacts were effectively identified, and identified contacts were effectively monitored and rapidly tested. There is a persistent risk of EVD reemergence in Liberia; the experience controlling each cluster can help inform future Ebola control efforts in Liberia and elsewhere., Author summary Contact tracing is one of the key response actions necessary for controlling spread of Ebola Virus Disease (EVD). Contact tracing is comprised of several different activities: identification of persons who have been in contact with confirmed EVD cases, close monitoring contacts for EVD symptoms, and management of symptomatic persons. Closely monitoring contacts of confirmed EVD cases allows for the rapid identification of symptomatic individuals, which in turn facilitates early testing, medical intervention, and isolation of new cases. This reduces the possibility of the continued spread of the virus within communities. Delayed and ineffective contact tracing contributed to the extensive transmission of EVD during the 2014–2015 outbreak in West Africa. Clusters of EVD reemergence are likely to occur, therefore understanding and addressing the challenges of implementing and managing contact tracing remains essential to halting transmission and minimizing morbidity and mortality associated with EVD. This paper assessed the contact tracing activities in response to EVD reemergence to identify best practices for responses to future Ebola clusters. The work is also applicable to contact tracing for other infectious diseases.

INTRODUCTION: Hand, foot, and mouth disease continues to cause seasonal epidemics in the Asia-Pacific Region. Since the current Enterovirus 71 vaccines do not provide cross-protection for all Enterovirus species that cause hand, foot, and mouth disease, there is an urgent need to identify appropriate detection tools and best practice to prevent its transmission and to effectively control its outbreaks. This systematic review aimed to identify characteristics of outbreak and assess the impact and effectiveness of detection tools and public health preventive measures to interrupt transmission. The findings will be used to recommend policy on the most effective responses and interventions in Hong Kong to effectively minimise and contain the spread of the disease within childcare facilities. METHODS: We searched the following databases for primary studies written in Chinese or English: MEDLINE, EMBASE, Global Health, WHO Western Pacific Region Index Medicus database, China National Knowledge Infrastructure Databases, and Chinese Scientific Journals Database. Studies conducted during or retrospective to outbreaks of hand, foot, and mouth disease caused by Enterovirus 71 from 1980 to 2012 within childcare facilities and with a study population of 0 to 6 years old were included. RESULTS: Sixteen studies conducted on outbreaks in China showed that hand, foot, and mouth disease spread rapidly within the facility, with an outbreak length of 4 to 46 days, especially in those with delayed notification (after 24 hours) of clustered outbreak (with five or more cases discovered within the facility) to the local Center for Disease Control and Prevention and delayed implementation of a control response. The number of classes affected ranged from 1 to 13, and the attack rate for children ranged from 0.97% to 28.18%. CONCLUSIONS: Communication between key stakeholders about outbreak confirmation, risk assessment, and surveillance should be improved. Effective communication facilitates timely notification (within 24 hours) of clustered outbreaks to a local Center for Disease Control and Prevention. Timely implementation of a control response is effective in minimising incidence and length of an outbreak in childcare facilities. The government should provide incentives for childcare facilities to train infection control specialists who can serve as the first contact, knowledge, and communication points, as well as facilitate exchange of information and provision of support across stakeholders during a communicable disease epidemic.

Alison Galvani and colleagues describe a community-based protocol to improve cooperation with Ebola testing as well as contact tracing, quarantining, and treatment.

Background The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. Methods and Findings Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola (“cases”) were asked if they had exposure to other potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO’s response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). Conclusions Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population., In this retrospective observational study, Christophe Fraser and colleagues analyze the exposure patterns associated with Ebola transmission during the 2013-2016 epidemic in West Africa., Author Summary Why Was This Study Done? Knowing how and from whom individuals acquire infection can help inform the response to limit the impact of an epidemic; this study presents updated versions of analyses initially performed to assist the international response during the 2013–2016 Ebola epidemic in West Africa. Over 19,000 individuals with confirmed or probable Ebola (“cases”) were reported in West Africa by 4 May 2015. Cases were asked whether they had exposure to potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. What Did the Researchers Do and Find? We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. Non-funeral exposures were strongly peaked around the time of death of the contact. There was evidence of super-spreading, with only 20% of cases accounting for at least 73% of new infections. What Do These Findings Mean? Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. The data are highly detailed despite the challenging circumstances in the three countries; however, the analyses were limited by data quality, mostly missing data and incorrect entries. In light of viral persistence in reservoirs, it is vital to maintain active surveillance and analysis of Ebola outbreaks to avoid and contain future outbreaks.

Purpose:\ud To investigate patterns of participation of visually impaired (VI) children and their families in health services research.\ud \ud Methods:\ud The authors compared clinical and sociodemographic characteristics of children and their families who participated with those who did not participate in two studies of quality of life (QoL) of VI children. In Study 1, the authors interviewed VI children and adolescents, aged 10 to 15 years, about their vision-related quality of life (VRQoL) as the first phase of a program to develop a VRQoL instrument for this population. One hundred seven children with visual impairment (visual acuity in the better eye LogMar worse than 0.51) were invited to participate in the interviews. Study 2 investigated health-related quality of life (HRQoL) of VI children using an existing generic instrument, administered in a postal survey. 151 VI children and adolescents, aged 2 to 16 years, with hereditary retinal disorders were invited to participate in the survey.\ud \ud Results:\ud The overall participation level was below 50%. In both studies, participants from white ethnic and more affluent socioeconomic backgrounds were overrepresented. Participation did not vary by age, sex, or clinical characteristics.\ud \ud Conclusions:\ud The authors suggest that there are barriers to participation in child- and family-centered research on childhood visual disability for children from socioeconomically deprived or ethnic minority groups. They urge assessment and reporting of participation patterns in further health services research on childhood visual disability. Failure to recognize that there are “silent voices” is likely to have important implications for equitable and appropriate service planning and provision for VI children.

Since January 2010 prospective strain typing on all positive TB samples able to be cultured has occurred. Recent infection is presumed if the strain of TB isolated from the case is indistinguishable from one or more others in the population studied. Recently infected cases are likely to be part of clusters. All data are currently preliminary. In London from January to September 2010, 2679 cases were reported to the London TB Register, 36% of which were culture confirmed. Of those that were culture confirmed 37% were in a cluster. Adults were more likely to be culture confirmed than children (37% vs 23%). While children may be less likely to be culture confirmed, those who were culture confirmed were more likely to be clustered (and so recently infected). Comparing children (0–15 year olds) to young adults (16–24 year olds), 70% compared to 40% were clustered (OR 3.49, p=0.003). Overall more clustering was noted among males (39% vs 33%, OR 1.28, p=0.08), white (40%) and black-Caribbean (47%) ethnic groups, UK born cases (42% vs 36%), and those with pulmonary (45% vs 30%) and sputum smear positive disease (56% vs 38%). More clustering was seen with those who had social risk factors: history of drug use (46%), homelessness (49%), imprisonment (47%), and alcohol abuse (46%). The majority were in clusters with

PURPOSE. Childhood-onset hereditary retinal disorders comprise a group of visually disabling conditions with variable onset and progression of visual impairment. Their impact on the health-related quality of life (HRQoL) of affected individuals, as well as the broader impact on their families has not been investigated previously.METHODS. In a cross-sectional study, a generic age-appropriate instrument, the PedsQL, was used to assess self-reported HRQoL in a subsample of a representative group of children with hereditary retinal disorders and their siblings as well as parental (proxy) assessment of HRQoL of their affected children. In addition, parents reported the broader impact and effect on functioning of the family using the PedsQL Family Impact Module.RESULTS. Affected children (n = 44) reported worse HRQoL than their unaffected siblings (n = 34) and notably, also worse scores than those reported by children with various serious chronic systemic disorders. On average, parents assessed their child's HRQoL to be worse than that self-reported by the child. There was an overall adverse impact on the family and its functioning, although siblings did not report impaired HRQoL themselves.CONCLUSIONS. This study demonstrates the significant impact, on both affected children and their families, of living with an untreatable, often progressive, and sometimes blinding ophthalmic disorder. It highlights the importance of support for affected individuals and their families, which may be targeted through use of generic or vision-related quality-of-life instruments for children as the latter become more widely available. Assessment of HRQoL would also be an important outcome measure in clinical trials of novel therapies for hereditary retinal disorders. (Invest Ophthalmol Vis Sci. 2011;52:7981-7986) DOI:10.1167/iovs.11-7890