Strengthening event-based surveillance (EBS): a case study from Afghanistan.

The sustained instability in Afghanistan, along with ongoing disease outbreaks and the impact of the COVID-19 pandemic, has significantly affected the country.During the COVID-19 pandemic, the country's detection and response capacities faced challenges. Case identification was done in all health facilities from primary to tertiary levels but neglected cases at the community level, resulting in undetected and uncontrolled transmission from communities. This emphasizes a missed opportunity for early detection that Event-Based Surveillance (EBS) could have facilitated.Therefore, Afghanistan planned to strengthen the EBS component of the national public health surveillance system to enhance the capacity for the rapid detection and response to infectious disease outbreaks, including COVID-19 and other emerging diseases. This effort was undertaken to promptly mitigate the impact of such outbreaks.We conducted a landscape assessment of Afghanistan's public health surveillance system to identify the best way to enhance EBS, and then we crafted an implementation work plan. The work plan included the following steps: establishing an EBS multisectoral coordination and working group, identifying EBS information sources, prioritizing public health events of importance, defining signals, establishing reporting mechanisms, and developing standard operating procedures and training guides.EBS is currently being piloted in seven provinces in Afghanistan. The lessons learned from the pilot phase will support its overall expansion throughout the country.

Achieving integrated disease surveillance in the Eastern Mediterranean Region.

Access to reliable and timely information is key for healthcare decision-making at the regional, national and sub-national levels. However, lack of access to such information hampers to progress towards achievement of the Sustainable Development Goals (SDGs) in the Eastern Mediterranean Region (EMR), as indicated in the Regional Progress Report on Health-Related Sustainable Development Goals.

Global public health intelligence: World Health Organization operational practices.

Early warning and response are key to tackle emerging and acute public health risks globally. Therefore, the World Health Organization (WHO) has implemented a robust approach to public health intelligence (PHI) for the global detection, verification and risk assessment of acute public health threats. WHO's PHI operations are underpinned by the International Health Regulations (2005), which require that countries strengthen surveillance efforts, and assess, notify and verify events that may constitute a public health emergency of international concern (PHEIC). PHI activities at WHO are conducted systematically at WHO's headquarters and all six regional offices continuously, throughout every day of the year. We describe four interlinked steps; detection, verification, risk assessment, and reporting and dissemination. For PHI operations, a diverse and interdisciplinary workforce is needed. Overall, PHI is a key feature of the global health architecture and will only become more prominent as the world faces increasing public health threats.

Participatory Mathematical Modeling Approach for Policymaking during the First Year of the COVID-19 Crisis, Jordan.

We engaged in a participatory modeling approach with health sector stakeholders in Jordan to support government decision-making regarding implementing public health measures to mitigate COVID-19 disease burden. We considered the effect of 4 physical distancing strategies on reducing COVID-19 transmission and mortality in Jordan during March 2020-January 2021: no physical distancing; intermittent physical distancing where all but essential services are closed once a week; intermittent physical distancing where all but essential services are closed twice a week; and a permanent physical distancing intervention. Modeling showed that the fourth strategy would be most effective in reducing cases and deaths; however, this approach was only marginally beneficial to reducing COVID-19 disease compared with an intermittently enforced physical distancing intervention. Scenario-based model influenced policy-making and the evolution of the pandemic in Jordan confirmed the forecasting provided by the modeling exercise and helped confirm the effectiveness of the policy adopted by the government of Jordan.

Mpox in Children and Adolescents during Multicountry Outbreak, 2022-2023.

The 2022-2023 mpox outbreak predominantly affected adult men; 1.3% of reported cases were in children and adolescents <18 years of age. Analysis of global surveillance data showed 1 hospital intensive care unit admission and 0 deaths in that age group. Transmission routes and clinical manifestations varied across age subgroups.

Baseline Seroprevalence of SARS-CoV-2 Specific Antibodies in Hot Spot Areas of Great Tunis, up to 3 Months Post Disease Onset in Tunisia.

The extent of the SARS-CoV-2 circulation and the COVID-19 epidemic in Tunisia three months after virus circulation was unknown. The aim of this study was to determine the extent of SARS-CoV-2 infection among household contacts of confirmed COVID-19 cases living in Hot spot areas of Great Tunis, Tunisia by estimating the seroprevalence of antibodies anti SARS-CoV-2 and to identify factors associated to seroprevalence at the first stage of the pandemic in order to guide decision making and to constitute a baseline for further longitudinal analysis of protective immunity to SARS-CoV-2. The National Observatory of New and Emerging Diseases (ONMNE), Ministry of Health Tunisia (MoH), with the support of the Office of the World Health Organization Representative in Tunisia and the WHO Regional Office for the Eastern Mediterranean (EMRO)), conducted a household cross-sectional survey on April 2020 in Great Tunis (Tunis, Ariana, Manouba and Ben Arous). The study was based on the WHO seroepidemiological investigation protocol for SARS-CoV-2 infection. SARS-CoV-2 specific antibodies (IgG and IgM) were qualitatively detected using a lateral immunoassay that detect SARS-CoV-2 nucleocapsid protein and administered by the interviewers. The included subjects were confirmed COVID-19 cases and their households contacts resided in hot spot areas (cumulative incidence rate ≥ 10 cases/100,000 inhabitants) of Great Tunis. Results: In total, 1165 subjects were enrolled: 116 confirmed COVID-19 cases (43 active cases and 73 convalescents cases) and 1049 household contacts resided in 291 households. The median age of participants was 39.0 with 31 years' interquartile range (Min = 8 months; Max = 96 years). The sex ratio (M/F) was 0.98. Twenty-nine per cent of participants resided in Tunis. The global crude seroprevalence among household contacts was 2.5% (26/1049); 95% CI 1.6-3.6%, 4.8%; 95% CI 2.3-8.7% in Ariana governorate and 0.3%; 95% CI 0.01%-1.8% in Manouba governorate. In multivariate analysis, the associated factors independently related to seroprevalence were age ≥25 years (aOR = 5.1; 95% CI 1.2-22.0), history of travel outside Tunisia since January 2020 (aOR = 4.6; 95% CI 1.7-12.9), symptomatic illness in the previous four months (aOR = 3.5; 95% CI 1.4-9.0) and governorate of residence (p = 0.02). The low seroprevalence estimated among household contacts in Great Tunis reflect the effect of public health measures early taken (national lockdown, borders closed, remote work), the respect of non-pharmaceutical interventions and the efficacy of COVID-19 contact-tracing and case management at the first stage of the pandemic in Tunisia.

Description of the first global outbreak of mpox: an analysis of global surveillance data.

BACKGROUND: In May 2022, several countries with no history of sustained community transmission of mpox (formerly known as monkeypox) notified WHO of new mpox cases. These cases were soon followed by a large-scale outbreak, which unfolded across the world, driven by local, in-country transmission within previously unaffected countries. On July 23, 2022, WHO declared the outbreak a Public Health Emergency of International Concern. Here, we aim to describe the main epidemiological features of this outbreak, the largest reported to date. METHODS: In this analysis of global surveillance data we analysed data for all confirmed mpox cases reported by WHO Member States through the global surveillance system from Jan 1, 2022, to Jan 29, 2023. Data included daily aggregated numbers of mpox cases by country and a case reporting form (CRF) containing information on demographics, clinical presentation, epidemiological exposure factors, and laboratory testing. We used the data to (1) describe the key epidemiological and clinical features of cases; (2) analyse risk factors for hospitalisation (by multivariable mixed-effects binary logistic regression); and (3) retrospectively analyse transmission trends. Sequencing data from GISAID and GenBank were used to analyse monkeypox virus (MPXV) genetic diversity. FINDINGS: Data from 82 807 cases with submitted CRFs were included in the analysis. Cases were primarily due to clade IIb MPXV (mainly lineage B.1, followed by lineage A.2). The outbreak was driven by transmission among males (73 560 [96·4%] of 76 293 cases) who self-identify as men who have sex with men (25 938 [86·9%] of 29 854 cases). The most common reported route of transmission was sexual contact (14 941 [68·7%] of 21 749). 3927 (7·3%) of 54 117 cases were hospitalised, with increased odds for those aged younger than 5 years (adjusted odds ratio 2·12 [95% CI 1·32-3·40], p=0·0020), aged 65 years and older (1·54 [1·05-2·25], p=0·026), female cases (1·61 [1·35-1·91], p<0·0001), and for cases who are immunosuppressed either due to being HIV positive and immunosuppressed (2·00 [1·68-2·37], p<0·0001), or other immunocompromising conditions (3·47 [1·84-6·54], p=0·0001). INTERPRETATION: Continued global surveillance allowed WHO to monitor the epidemic, identify risk factors, and inform the public health response. The outbreak can be attributed to clade IIb MPXV spread by newly described modes of transmission. FUNDING: WHO Contingency Fund for Emergencies. TRANSLATIONS: For the French and Spanish translations of the abstract see Supplementary Materials section.

Usage of social media in epidemic intelligence activities in the WHO, Regional Office for the Eastern Mediterranean.

Social media platforms are a massive source of information being used for monitoring and detecting various actual events such as natural disasters and disease outbreaks. This paper aims to present the experience of WHO, Regional Office for the Eastern Mediterranean in using social media for the detection and monitoring of COVD-19 pandemic alongside the other event-based surveillance tools. Over the period of 29 January 2020 to 31 May 2021, information was collected from social media and other media outlets (web news) as being the source of health information for early detecting and monitoring the situation of COVID-19 events. Signals were categorised into new events and event updates; where event updates captured from social media were categorised into official and unofficial. A total of 10 160 COVID-19 information were captured, out of which 95.8% (n=9732) were detected through social media. None of the information captured were discarded. 50.0% (n=11) of the COVID-19 events in the Eastern Mediterranean Region (EMR) were primarily captured from social media compared with 4.5% (n=1) primarily captured from other media outlets. Almost all (99.4%) of the event updates captured from social media were official updates. Real-time, transparent and relevant information posted on different social media platforms, especially the governmental official social media accounts, strengthened the early detection and follow-up of public health events in the EMR, especially during the current COVID-19 pandemic.

Contact tracing in the context of COVID-19: a case study from Oman.

In April 2020, the Ministry of Health (MoH) in Oman, a high-income country in the Eastern Mediterranean Region (EMR), implemented a robust contact tracing (CT) system for COVID-19. To capitalise on Oman's experience, EMRO has developed a case study presenting the methodology used to conduct the CT activities, main functions of the system, challenges encountered, lessons learnt, and the way forward. To develop the case study, a key informant interview was conducted virtually with the CT focal point in the MoH, using a semistructured questionnaire adapted from the WHO questionnaire for the assessment of CT activities. The Oman MoH launched a CT system based on three complementary digital tools: Tarassud plus, Medical Scout and HMushrif applications. Oman's CT strategy classifies contacts into close and casual contacts. Only close contacts are listed using the Tarassud plus application, while casual contacts are requested to self-monitor for 14 days using the other two applications. With the evolution of the outbreak, Oman MoH implemented stricter policies and prioritised the follow-up of close contacts to keep the CT activity manageable. Community health workers and volunteers facilitated the CT activities through sensitisation of the local community to the follow-up process and reducing the COVID-19-associated stigma. Challenges encountered revolved around contact data management, given the offline in-operability of the applications, and lack of national risk communication guidelines to address community concerns and widespread rumours.

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward.

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks.

The World Health Organization's public health intelligence activities during the COVID-19 pandemic response, December 2019 to December 2021.

The coronavirus disease (COVID-19) presented a unique opportunity for the World Health Organization (WHO) to utilise public health intelligence (PHI) for pandemic response. WHO systematically captured mainly unstructured information (e.g. media articles, listservs, community-based reporting) for public health intelligence purposes. WHO used the Epidemic Intelligence from Open Sources (EIOS) system as one of the information sources for PHI. The processes and scope for PHI were adapted as the pandemic evolved and tailored to regional response needs. During the early months of the pandemic, media monitoring complemented official case and death reporting through the International Health Regulations mechanism and triggered alerts. As the pandemic evolved, PHI activities prioritised identifying epidemiological trends to supplement the information available through indicator-based surveillance reported to WHO. The PHI scope evolved over time to include vaccine introduction, emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, unusual clinical manifestations and upsurges in cases, hospitalisation and death incidences at subnational levels. Triaging the unprecedented high volume of information challenged surveillance activities but was managed by collaborative information sharing. The evolution of PHI activities using multiple sources in WHO's response to the COVID-19 pandemic illustrates the future directions in which PHI methodologies could be developed and used.

A participatory modelling approach for investigating the spread of COVID-19 in countries of the Eastern Mediterranean Region to support public health decision-making.

Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker's perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states.

Case study of Argus in Togo: An SMS and web-based application to support public health surveillance, results from 2016 to 2019.

INTRODUCTION: Argus is an open source electronic solution to facilitate the reporting and management of public health surveillance data. Its components include an Android-phone application, used by healthcare facilities to report results via SMS; and a central server located at the Ministry of Health, displaying aggregated results on a web platform for intermediate and central levels. This study describes the results of the use of Argus in two regions of Togo. METHODS: Argus was used in 148 healthcare facilities from May 2016 to July 2018, expanding to 185 healthcare facilities from July 2018. Data from week 21 of 2016 to week 12 of 2019 was extracted from the Argus database and analysed. An assessment mission took place in August 2016 to collect users' satisfaction, to estimate the concordance of the received data with the collected data, and to estimate the time required to report data with Argus. RESULTS: Overall completeness of data reporting was 76%, with 80% of reports from a given week being received before Tuesday 9PM. Concordance of data received from Argus and standard paper forms was 99.7%. Median time needed to send a report using Argus was 4 minutes. Overall completeness of data review at district, regional, and central levels were 89%, 68%, and 35% respectively. Implementation cost of Argus was 23 760 USD for 148 facilities. CONCLUSIONS: The use of Argus in Togo enabled healthcare facilities to send weekly reports and alerts through SMS in a user-friendly, reliable and timely manner. Reengagement of surveillance officers at all levels, especially at the central level, enabled a dramatic increase in completeness and timeliness of data report and data review.

Health consequences of drought in the WHO Eastern Mediterranean Region: hotspot areas and needed actions.

BACKGROUND: Over the past four decades, drought episodes in the Eastern Mediterranean Region (EMR) of the of the World Health Organization (WHO) have gradually become more widespread, prolonged and frequent. We aimed to map hotspot countries and identified key strategic actions for health consequences. METHODS: We reviewed scientific literature and WHO EMR documentation on trends and patterns of the drought health consequences from 1990 through 2019. Extensive communication was also carried out with EMR WHO country offices to retrieve information on ongoing initiatives to face health consequences due to drought. An index score was developed to categorize countries according vulnerability factors towards drought. RESULTS: A series of complex health consequences are due to drought in EMR, including malnutrition, vector-borne diseases, and water-borne diseases. The index score indicated how Afghanistan, Yemen and Somalia are "hotspots" due to poor population health status and access to basic sanitation as well as other elements such as food insecurity, displacement and conflicts/political instability. WHO country offices effort is towards enhancing access to water and sanitation and essential healthcare services including immunization and psychological support, strengthening disease surveillance and response, and risk communication. CONCLUSIONS: Drought-related health effects in the WHO EMR represent a public health emergency. Strengthening mitigation activities and additional tailored efforts are urgently needed to overcome context-specific gaps and weaknesses, with specific focus on financing, accountability and enhanced data availability.

SMS-based smartphone application for disease surveillance has doubled completeness and timeliness in a limited-resource setting - evaluation of a 15-week pilot program in Central African Republic (CAR).

BACKGROUND: It is a challenge in low-resource settings to ensure the availability of complete, timely disease surveillance information. Smartphone applications (apps) have the potential to enhance surveillance data transmission. METHODS: The Central African Republic (CAR) Ministry of Health and Médecins Sans Frontières (MSF) conducted a 15-week pilot project to test a disease surveillance app, Argus, for 20 conditions in 21 health centers in Mambéré Kadéi district (MK 2016). Results were compared to the usual paper-based surveillance in MK the year prior (MK 2015) and simultaneously in an adjacent health district, Nana-Mambére (NM 2016). Wilcoxon rank sum and Kaplan-Meier analyses compared report completeness and timeliness; the cost of the app, and users' perceptions of its usability were assessed. RESULTS: Two hundred seventy-one weekly reports sent by app identified 3403 cases and 63 deaths; 15 alerts identified 28 cases and 4 deaths. Median completeness (IQR) for MK 2016, 81% (81-86%), was significantly higher than in MK 2015 (31% (24-36%)), and NM 2016 (52% (48-57)) (p < 0.01). Median timeliness (IQR) for MK 2016, 50% (39-57%) was also higher than in MK 2015, 19% (19-24%), and NM 2016 29% (24-36%) (p < 0.01). Kaplan-Meier Survival Analysis showed a significant progressive reduction in the time taken to transmit reports over the 15-week period (p < 0.01). Users ranked the app's usability as greater than 4/5 on all dimensions. The total cost of the 15-week pilot project was US$40,575. It is estimated that to maintain the app in the 21 health facilities of MK will cost approximately US$18,800 in communication fees per year. CONCLUSIONS: The app-based data transmission system more than doubled the completeness and timeliness of disease surveillance reports. This simple, low-cost intervention may permit the early detection of disease outbreaks in similar low-resource settings elsewhere.

Ebola epidemic--Liberia, March-October 2014.

On March 21, 2014, the Guinea Ministry of Health reported the outbreak of an illness characterized by fever, severe diarrhea, vomiting and a high fatality rate (59%), leading to the first known epidemic of Ebola virus disease (Ebola) in West Africa and the largest and longest Ebola epidemic in history. As of November 2, Liberia had reported the largest number of cases (6,525) and deaths (2,697) among the three affected countries of West Africa with ongoing transmission (Guinea, Liberia, and Sierra Leone). The response strategy in Liberia has included management of the epidemic through an incident management system (IMS) in which the activities of all partners are coordinated. Within the IMS, key strategies for epidemic control include surveillance, case investigation, laboratory confirmation, contact tracing, safe transportation of persons with suspected Ebola, isolation, infection control within the health care system, community engagement, and safe burial. This report provides a brief overview of the progression of the epidemic in Liberia and summarizes the interventions implemented.