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High-quality vaccine-preventable disease (VPD) surveillance data are critical for timely outbreak detection and response. In 2019, the World Health Organization (WHO) African Regional Office (AFRO) began transitioning from Epi Info, a free, CDC-developed statistical software package with limited capability to integrate with other information systems, affecting reporting timeliness and data use, to District Health Information Software 2 (DHIS2). DHIS2 is a free and open-source software platform for electronic aggregate Integrated Disease Surveillance and Response (IDSR) and case-based surveillance reporting. A national-level reporting system, which provided countries with the option to adopt this new system, was introduced. Regionally, the Epi Info database will be replaced with a DHIS2 regional data platform. This report describes the phased implementation from 2019 to the present. Phase one (2019-2021) involved developing IDSR aggregate and case-based surveillance packages, including pilots in the countries of Mali, Rwanda, and Togo. Phase two (2022) expanded national-level implementation to 27 countries and established the WHO AFRO DHIS2 regional data platform. Phase three (from 2023 to the present) activities have been building local capacity and support for country reporting to the regional platform. By February 2024, eight of 47 AFRO countries had adopted both the aggregate IDSR and case-based surveillance packages, and two had successfully transferred VPD surveillance data to the AFRO regional platform. Challenges included limited human and financial resources, the need to establish data-sharing and governance agreements, technical support for data transfer, and building local capacity to report to the regional platform. Despite these challenges, the transition to DHIS2 will support efficient data transmission to strengthen VPD detection, response, and public health emergencies through improved system integration and interoperability., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

The COVID-19 pandemic challenged countries to protect their populations from this emerging disease. One aspect of that challenge was to rapidly modify national surveillance systems or create new systems that would effectively detect new cases of COVID-19. Fifty-five countries leveraged past investments in District Health Information Software version 2 (DHIS2) to quickly adapt their national public health surveillance systems for COVID-19 case reporting and response activities. We provide background on DHIS2 and describe case studies from Sierra Leone, Sri Lanka, and Uganda to illustrate how the DHIS2 platform, its community of practice, long-term capacity building, and local autonomy enabled countries to establish an effective COVID-19 response. With these case studies, we provide valuable insights and recommendations for strategies that can be used for national electronic disease surveillance platforms to detect new and emerging pathogens and respond to public health emergencies.

On April 25, 2017, the Sinoe County Health Team (CHT) notified the Liberia Ministry of Health (MoH) and the National Public Health Institute of Liberia of an unknown illness among 14 persons that resulted in eight deaths in Sinoe County. On April 26, the National Rapid Response Team and epidemiologists from CDC, the World Health Organization (WHO) and the African Field Epidemiology Network (AFENET) in Liberia were deployed to support the county-led response. Measures were immediately implemented to identify all cases, ascertain the cause of illness, and control the outbreak. Illness was associated with attendance at a funeral event, and laboratory testing confirmed Neisseria meningitidis in biologic specimens from cases. The 2014-2015 Ebola virus disease (Ebola) outbreak in West Africa devastated Liberia's already fragile health system, and it took many months for the country to mount an effective response to control the outbreak. Substantial efforts have been made to strengthen Liberia's health system to prevent, detect, and respond to health threats. The rapid and efficient field response to this outbreak of N. meningitidis resulted in implementation of appropriate steps to prevent a widespread outbreak and reflects improved public health and outbreak response capacity in Liberia.

As one of the three West African countries highly affected by the 2014-2015 Ebola virus disease (Ebola) epidemic, Liberia reported approximately 10,000 cases. The Ebola epidemic in Liberia was marked by intense urban transmission, multiple community outbreaks with source cases occurring in patients coming from the urban areas, and outbreaks in health care facilities (HCFs). This report, based on data from routine case investigations and contact tracing, describes efforts to stop the last known chain of Ebola transmission in Liberia. The index patient became ill on December 29, 2014, and the last of 21 associated cases was in a patient admitted into an Ebola treatment unit (ETU) on February 18, 2015. The chain of transmission was stopped because of early detection of new cases; identification, monitoring, and support of contacts in acceptable settings; effective triage within the health care system; and rapid isolation of symptomatic contacts. In addition, a "sector" approach, which divided Montserrado County into geographic units, facilitated the ability of response teams to rapidly respond to community needs. In the final stages of the outbreak, intensive coordination among partners and engagement of community leaders were needed to stop transmission in densely populated Montserrado County. A companion report describes the efforts to enhance infection prevention and control efforts in HCFs. After February 19, no additional clusters of Ebola cases have been detected in Liberia. On May 9, the World Health Organization declared the end of the Ebola outbreak in Liberia.

Background: For disease surveillance, manual data collection using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphone data collection to replace paper-based data collection for an influenza sentinel surveillance system in four hospitals in Kenya. We compared the quality, cost and timeliness of data collection between the smartphone data collection system and the paper-based system., Methods: Since 2006, the Kenya Ministry of Health (MoH) with technical support from the Kenya Medical Research Institute/Centers for Disease Control and Prevention (KEMRI/CDC) conducted hospital-based sentinel surveillance for influenza in Kenya. In May 2011, the MOH replaced paper-based collection with an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. We compared 880 paper-based questionnaires dated Jan 2010-Jun 2011 and 880 smartphone questionnaires dated May 2011-Jun 2012 from the four surveillance sites. For each site, we compared the quality, cost and timeliness of each data collection system., Results: Incomplete records were more likely seen in data collected using pen-and-paper compared to data collected using smartphones (adjusted incidence rate ratio (aIRR) 7, 95% CI: 4.4-10.3). Errors and inconsistent answers were also more likely to be seen in data collected using pen-and-paper compared to data collected using smartphones (aIRR: 25, 95% CI: 12.5-51.8). Smartphone data was uploaded into the database in a median time of 7 days while paper-based data took a median of 21 days to be entered (p < 0.01). It cost USD 1,501 (9.4%) more to establish the smartphone data collection system ($17,500) than the pen-and-paper system (USD $15,999). During two years, however, the smartphone data collection system was $3,801 (7%) less expensive to operate ($50,200) when compared to pen-and-paper system ($54,001)., Conclusions: Compared to paper-based data collection, an electronic data collection system produced fewer incomplete data, fewer errors and inconsistent responses and delivered data faster. Although start-up costs were higher, the overall costs of establishing and running the electronic data collection system were lower compared to paper-based data collection system. Electronic data collection using smartphones has potential to improve timeliness, data integrity and reduce costs.

Over the past decade, Vietnam has successfully responded to global health security (GHS) challenges, including domestic elimination of severe acute respiratory syndrome (SARS) and rapid public health responses to human infections with influenza A(H5N1) virus. However, new threats such as Middle East respiratory syndrome coronavirus (MERS-CoV) and influenza A(H7N9) present continued challenges, reinforcing the need to improve the global capacity to prevent, detect, and respond to public health threats. In June 2012, Vietnam, along with many other nations, obtained a 2-year extension for meeting core surveillance and response requirements of the 2005 International Health Regulations (IHR). During March-September 2013, CDC and the Vietnamese Ministry of Health (MoH) collaborated on a GHS demonstration project to improve public health emergency detection and response capacity. The project aimed to demonstrate, in a short period, that enhancements to Vietnam's health system in surveillance and early detection of and response to diseases and outbreaks could contribute to meeting the IHR core capacities, consistent with the Asia Pacific Strategy for Emerging Diseases. Work focused on enhancements to three interrelated priority areas and included achievements in 1) establishing an emergency operations center (EOC) at the General Department of Preventive Medicine with training of personnel for public health emergency management; 2) improving the nationwide laboratory system, including enhanced testing capability for several priority pathogens (i.e., those in Vietnam most likely to contribute to public health emergencies of international concern); and 3) creating an emergency response information systems platform, including a demonstration of real-time reporting capability. Lessons learned included awareness that integrated functions within the health system for GHS require careful planning, stakeholder buy-in, and intradepartmental and interdepartmental coordination and communication.

We estimated Rift Valley fever (RVF) incidence as a function of geological, geographical, and climatological factors during the 2006-2007 RVF epidemic in Kenya. Location information was obtained for 214 of 340 (63%) confirmed and probable RVF cases that occurred during an outbreak from November 1, 2006 to February 28, 2007. Locations with subtypes of solonetz, calcisols, solonchaks, and planosols soil types were highly associated with RVF occurrence during the outbreak period. Increased rainfall and higher greenness measures before the outbreak were associated with increased risk. RVF was more likely to occur on plains, in densely bushed areas, at lower elevations, and in the Somalia acacia ecological zone. Cases occurred in three spatial temporal clusters that differed by the date of associated rainfall, soil type, and land usage.