On August 1, 2018, the Democratic Republic of the Congo Ministry of Health (DRC MoH) declared the tenth outbreak of Ebola virus disease (Ebola) in DRC, in the North Kivu province in eastern DRC on the border with Uganda, 8 days after another Ebola outbreak was declared over in northwest Équateur province. During mid- to late-July 2018, a cluster of 26 cases of acute hemorrhagic fever, including 20 deaths, was reported in North Kivu province.* Blood specimens from six patients hospitalized in the Mabalako health zone and sent to the Institut National de Recherche Biomédicale (National Biomedical Research Institute) in Kinshasa tested positive for Ebola virus. Genetic sequencing confirmed that the outbreaks in North Kivu and Équateur provinces were unrelated. From North Kivu province, the outbreak spread north to Ituri province, and south to South Kivu province (1). On July 17, 2019, the World Health Organization designated the North Kivu and Ituri outbreak a public health emergency of international concern, based on the geographic spread of the disease to Goma, the capital of North Kivu province, and to Uganda and the challenges to implementing prevention and control measures specific to this region (2). This report describes the outbreak in the North Kivu and Ituri provinces. As of November 17, 2019, a total of 3,296 Ebola cases and 2,196 (67%) deaths were reported, making this the second largest documented outbreak after the 2014-2016 epidemic in West Africa, which resulted in 28,600 cases and 11,325 deaths.(†) Since August 2018, DRC MoH has been collaborating with partners, including the World Health Organization, the United Nations Children's Fund, the United Nations Office for the Coordination of Humanitarian Affairs, the International Organization of Migration, The Alliance for International Medical Action (ALIMA), Médecins Sans Frontières, DRC Red Cross National Society, and CDC, to control the outbreak. Enhanced communication and effective community engagement, timing of interventions during periods of relative stability, and intensive training of local residents to manage response activities with periodic supervision by national and international personnel are needed to end the outbreak.

Kenya's Ministry of Health (MOH) and the US Centers for Disease Control and Prevention in Kenya (CDC Kenya) have maintained a 40-year partnership during which measures were implemented to prevent, detect, and respond to disease threats. During the COVID-19 pandemic, the MOH and CDC Kenya rapidly responded to mitigate disease impact on Kenya's 52 million residents. We describe activities undertaken jointly by the MOH and CDC Kenya that lessened the effects of COVID-19 during 5 epidemic waves from March through December 2021. Activities included establishing national and county-level emergency operations centers and implementing workforce development and deployment, infection prevention and control training, laboratory diagnostic advancement, enhanced surveillance, and information management. The COVID-19 pandemic provided fresh impetus for the government of Kenya to establish a national public health institute, launched in January 2022, to consolidate its public health activities and counter COVID-19 and future infectious, vaccine-preventable, and emerging zoonotic diseases.

BACKGROUND: In resource-limited settings, underlying causes of death (UCOD) often are not ascertained systematically, leading to unreliable mortality statistics. We reviewed medical charts to establish UCOD for decedents at two high volume mortuaries in Kisumu County, Kenya, and compared ascertained UCOD to those notified to the civil registry. METHODS: Medical experts trained in COD certification examined medical charts and ascertained causes of death for 456 decedents admitted to the mortuaries from April 16 through July 12, 2019. Decedents with unknown HIV status or who had tested HIV-negative >90 days before the date of death were tested for HIV. We calculated annualized all-cause and cause-specific mortality rates grouped according to global burden of disease (GBD) categories and separately for deaths due to HIV/AIDS and expressed estimated deaths per 100,000 population. We compared notified to ascertained UCOD using Cohen's Kappa (κ) and assessed for the independence of proportions using Pearson's chi-squared test. FINDINGS: The four leading UCOD were HIV/AIDS (102/442 [23.1%]), hypertensive disease (41/442 [9.3%]), other cardiovascular diseases (23/442 [5.2%]), and cancer (20/442 [4.5%]). The all-cause mortality rate was 1,086/100,000 population. The highest cause-specific mortality was in GBD category II (noncommunicable diseases; 516/100,000), followed by GBD I (communicable, perinatal, maternal, and nutritional; 513/100,000), and III (injuries; 56/100,000). The HIV/AIDS mortality rate was 251/100,000 population. The proportion of deaths due to GBD II causes was higher among females (51.9%) than male decedents (42.1%; p = 0.039). Conversely, more men/boys (8.6%) than women/girls (2.1%) died of GBD III causes (p = 0.002). Most of the records with available recorded and ascertained UCOD (n = 236), 167 (70.8%) had incorrectly recorded UCOD, and agreement between notified and ascertained UCOD was poor (29.2%; κ = 0.26). CONCLUSIONS: Mortality from infectious diseases, especially HIV/AIDS, is high in Kisumu County, but there is a shift toward higher mortality from noncommunicable diseases, possibly reflecting an epidemiologic transition and improving HIV outcomes. The epidemiologic transition suggests the need for increased focus on controlling noncommunicable conditions despite the high communicable disease burden. The weak agreement between notified and ascertained UCOD could lead to substantial inaccuracies in mortality statistics, which wholly depend on death notifications.

BACKGROUND: HIV is a major driver of the tuberculosis epidemic in sub-Saharan Africa. The population-level impact of antiretroviral therapy (ART) scale-up on tuberculosis rates in this region has not been well studied. We conducted a descriptive analysis to examine evidence of population-level effect of ART on tuberculosis by comparing trends in estimated tuberculosis notification rates, by HIV status, for countries in sub-Saharan Africa. METHODS: We estimated annual tuberculosis notification rates, stratified by HIV status during 2010-2015 using data from WHO, the Joint United Nations Programme on HIV/AIDS, and the United Nations Population Division. Countries were included in this analysis if they had >/=4 years of HIV prevalence estimates and >/= 75% of tuberculosis patients with known HIV status. We compared tuberculosis notification rates among people living with HIV (PLHIV) and people without HIV via Wilcoxon rank sum test. RESULTS: Among 23 included countries, the median annual average change in tuberculosis notification rates among PLHIV during 2010-2015 was -5.7% (IQR -6.9 to -1.7%), compared to a median change of -2.3% (IQR -4.2 to -0.1%) among people without HIV (p-value = 0.0099). Among 11 countries with higher ART coverage, the median annual average change in TB notification rates among PLHIV was -6.8% (IQR -7.6 to -5.7%) compared to a median change of -2.1% (IQR -6.0 to 0.7%) for PLHIV in 12 countries with lower ART coverage (p = 0.0106). CONCLUSION: Tuberculosis notification rates declined more among PLHIV than people without HIV, and have declined more in countries with higher ART coverage. These results are consistent with a population-level effect of ART on decreasing TB incidence among PLHIV. To further reduce TB incidence among PLHIV, additional scale-up of ART as well as greater use of isoniazid preventive therapy and active case-finding will be necessary.

Dadaab Refugee camp in Garissa County, Kenya, hosts nearly 340,000 refugees in five subcamps (Dagahaley, Hagadera, Ifo, Ifo2, and Kambioos) (1). On November 18 and 19, 2015, during an ongoing national cholera outbreak (2), two camp residents were evaluated for acute watery diarrhea (three or more stools in </=24 hours); Vibrio cholerae serogroup O1 serotype Ogawa was isolated from stool specimens collected from both patients. Within 1 week of the report of index cases, an additional 45 cases of acute watery diarrhea were reported. The United Nations High Commissioner for Refugees and their health-sector partners coordinated the cholera response, community outreach and water, sanitation, and hygiene (WASH) activities; Medecins Sans Frontieres and the International Rescue Committee were involved in management of cholera treatment centers; CDC performed laboratory confirmation of cases and undertook GIS mapping and postoutbreak response assessment; and the Garissa County Government and the Kenya Ministry of Health conducted a case-control study. To prevent future cholera outbreaks, improvements to WASH and enhanced disease surveillance systems in Dadaab camp and the surrounding area are needed.

OBJECTIVES: Estimating HIV incidence is critical for identifying groups at risk for HIV infection, planning and targeting interventions, and evaluating these interventions over time. The use of reliable estimation methods for HIV incidence is thus of high importance. The aim of this study was to compare methods for estimating HIV incidence in a population-based cross-sectional survey. DESIGN/METHODS: The incidence estimation methods evaluated included assay-derived methods, a testing history-derived method, and a probability-based method applied to data from the Ndhiwa HIV Impact in Population Survey (NHIPS). Incidence rates by sex and age and cumulative incidence as a function of age were presented. RESULTS: HIV incidence ranged from 1.38 [95% confidence interval (CI) 0.67-2.09] to 3.30 [95% CI 2.78-3.82] per 100 persons-years overall; 0.59 [95% CI 0.00-1.34] to 2.89 [95% CI 0.11-5.68] in men; and 1.62 [95% CI 0.16-6.04] to 4.03 [95% CI 3.30-4.77] per 100 persons-years in women. Women had higher incidence rates than men for all methods. Incidence rates were highest among women aged 15-24 and 25-34 years and highest among men aged 25-34 years. CONCLUSION: Comparison of different methods showed variations in incidence estimates, but they were in agreement to identify most-at-risk groups. The use and comparison of several distinct approaches for estimating incidence are important to provide the best-supported estimate of HIV incidence in the population.

Persons who died of Ebola virus disease at home in rural communities in Liberia and Guinea resulted in more secondary infections than persons admitted to Ebola treatment units. Intensified monitoring of contacts of persons who died of this disease in the community is an evidence-based approach to reduce virus transmission in rural communities.

Extraordinary progress has been achieved in confronting the global HIV epidemic. The number of people living with HIV (PLWH) accessing antiretroviral treatment (ART) in low- and middle-income countries rose from 400,000 in 2003 to 17 million in 2015,1 and an estimated 7.8 million deaths have been averted by the scale-up of ART services.2 Increased access to prevention and treatment has also led to a 35% drop in new HIV infections since 2000, including a 58% decrease amongst children.3 | The majority of PLWH accessing ART in low-resource settings live in sub Saharan Africa, a region with some of the world’s weakest health systems. Despite austere settings, health worker shortages, dysfunctional supply chains and laboratories, and absent continuity care systems, the HIV response has succeeded beyond expectations.4 Although this success was built on the use of simple, standardized, and evidence-based approaches to HIV prevention and treatment, new global guidelines support the use of more individualized services.5 While such a differentiated care strategy has the potential to improve both the quality and efficiency of HIV programs, this can only be accomplished if key elements of the public health approach that has been so successful over the past 20 years are retained.

We measured the reproduction number before and after interventions were implemented to reduce Ebola transmission in 9 outbreaks in Liberia during 2014. We evaluated risk factors for secondary cases and the association between patient admission to an Ebola treatment unit (ETU) and survival. The reproduction number declined 94% from 1.7 (95% CI 1.1-2.6) to 0.1 (95% CI 0.02-0.6) after interventions began. The risk for secondary infections was 90% lower for patients admitted to an ETU (risk ratio 0.1, 95% CI 0.04-0.3) than for those who died in the community. The case-fatality rate was 68% (95% CI 60-74), and ETU admission was associated with a 50% reduction in death (hazard ratio 0.5, 95% CI 0.4-0.8). Isolation and treatment of Ebola patients had the dual benefit of interrupting community transmission and improving survival.

West Africa is experiencing its first epidemic of Ebola virus disease (Ebola). As of February 9, Liberia has reported 8,864 Ebola cases, of which 3,147 were laboratory-confirmed. Beginning in August 2014, the Liberia Ministry of Health and Social Welfare (MOHSW), supported by CDC, the World Health Organization (WHO), and others, began systematically investigating and responding to Ebola outbreaks in remote areas. Because many of these areas lacked mobile telephone service, easy road access, and basic infrastructure, flexible and targeted interventions often were required. Development of a national strategy for the Rapid Isolation and Treatment of Ebola (RITE) began in early October. The strategy focuses on enhancing capacity of county health teams (CHT) to investigate outbreaks in remote areas and lead tailored responses through effective and efficient coordination of technical and operational assistance from the MOHSW central level and international partners. To measure improvements in response indicators and outcomes over time, data from investigations of 12 of 15 outbreaks in remote areas with illness onset dates of index cases during July 16-November 20, 2014, were analyzed. The times to initial outbreak alerts and durations of the outbreaks declined over that period while the proportions of patients who were isolated and treated increased. At the same time, the case-fatality rate in each outbreak declined. Implementation of strategies, such as RITE, to rapidly respond to rural outbreaks of Ebola through coordinated and tailored responses can successfullyreduce transmission and improve outcomes.

On October 16, 2014, a woman aged 48 years traveled from Monrovia, Liberia, to the Kayah region of Rivercess County, a remote, resource-poor, and sparsely populated region of Liberia, and died on October 21 with symptoms compatible with Ebola virus disease (Ebola). She was buried in accordance with local tradition, which included grooming, touching, and kissing the body by family and other community members while it was being prepared for burial. During October 24-November 12, eight persons with probable and 13 with confirmed Ebola epidemiologically linked to the deceased woman had onset of symptoms. Nineteen of the 21 persons lived in five nearby villages in Kayah region; two, both with probable cases, lived in neighboring Grand Bassa County (Figure). Four of the confirmed cases in Kayah were linked by time and location, although the source case could not be determined because the patients had more than one exposure.

In September 2011, the United Nations (UN) convened a High Level Meeting (HLM) of member states to address a largely neglected, global reality: Noncommunicable diseases (NCDs)—including heart disease, stroke, cancer, diabetes, and chronic lung diseases—kill more people than other causes, health and non–health related, and the world is ill-prepared to respond. This was only the second such UN meeting of heads of state focused on a health issue, the first having been on HIV/AIDS in 2001. Without more effective and focused action, the growing burden of NCDs threatens to undermine increasingly interdependent development and economic agendas (1–3). The 2011 meeting ushered in the potential for an orchestrated response, facilitated by a mandate that the World Health Organization (WHO), in consultation with member states, develop a global monitoring framework with key indicators and targets to be achieved by 2025. | The task is to be completed by the end of 2012 (1). Only one global voluntary indicator with a target has received formal member-state endorsement thus far: reduce the probability of premature mortality from NCDs by 25% by 2025. Another 10 indicators with targets, and 9 indicators without targets, are proposed and under development (2), with the deadline just months away.

The KEMRI/Centers for Disease Control and Prevention (CDC) Health and Demographic Surveillance System (HDSS) is located in Rarieda, Siaya and Gem Districts (Siaya County), lying northeast of Lake Victoria in Nyanza Province, western Kenya. The KEMRI/CDC HDSS, with approximately 220 000 inhabitants, has been the foundation for a variety of studies, including evaluations of insecticide-treated bed nets, burden of diarrhoeal disease and tuberculosis, malaria parasitaemia and anaemia, treatment strategies and immunological correlates of malaria infection, and numerous HIV, tuberculosis, malaria and diarrhoeal disease treatment and vaccine efficacy and effectiveness trials for more than a decade. Current studies include operations research to measure the uptake and effectiveness of the programmatic implementation of integrated malaria control strategies, HIV services, newly introduced vaccines and clinical trials. The HDSS provides general demographic and health information (such as population age structure and density, fertility rates, birth and death rates, in- and out-migrations, patterns of health care access and utilization and the local economics of health care) as well as disease- or intervention-specific information. The HDSS also collects verbal autopsy information on all deaths. Studies take advantage of the sampling frame inherent in the HDSS, whether at individual, household/compound or neighbourhood level.

The history of the HIV epidemic and the response to the epidemic is fundamentally a history of an emergency response to a global crisis. Trends and projections from initially available data were instrumental in establishing the President's Emergency Plan for AIDS Relief (PEPFAR) and in determining the direction of the program. Additionally, PEPFAR was built on data and the potential impact of interventions, and required the constant monitoring of the epidemic to report on the progress of the program. The response to the HIV epidemic saw the development of international guidelines and recommendations for data collection and epidemiological modeling. Although it is true that the urgency of the response often meant that data from data-poor countries suffered from incompleteness and bias, fortunately, as the response matured, the quality of the data and the infrastructure supporting data collection also matured. PEPFAR investments in surveillance and surveys were and remain critical for responding to the epidemic. The future of the response is reflected in growing country capacities to collect valid and reliable data, and using those data for decision making.

In late August 2007, Dr. Peter Kilmarx, a CDC epidemiologist working on HIV/AIDS, awoke at his home in Atlanta to read a text message on his mobile phone. The message, sent the night before, was from Gilbert Shamba Mayi, the chief of Bakawa Tombe, a small village in Kasai Occidental Province in the Democratic Republic of Congo. Dr. Kilmarx had met the chief approximately 20 years earlier while serving in the Peace Corps. The message said in a local Congolese language, "Bakwa Tombe greets you with pleasure. There is a lot of death from Ebola. When are you coming for the hospital? How are you Peter? Chief Gilbert Shamba Mayi." | | This real time text message from a "citizen epidemiologist" in a remote Congolese village led to deployment of a CDC team to the affected area in less than 2 weeks, and they determined quickly that the cause of the outbreak was Ebola hemorrhagic fever. Compare this anecdote to an experience of the author of this article, Dr. Kevin DeCock, while he was an Epidemic Intelligence Service Officer 21 years earlier in 1986. A severe outbreak of yellow fever started in Benue State, Nigeria, during the middle of 1986 and had already peaked by the time it came to national attention in October of that year. An outbreak investigation by an international team began in December. By the time the international team arrived, approximately 40,000 yellow fever infections and 5,000 deaths had already occurred (1).

BACKGROUND: There is need for locally-derived age-specific clinical laboratory reference ranges of healthy Africans in sub-Saharan Africa. Reference values from North American and European populations are being used for African subjects despite previous studies showing significant differences. Our aim was to establish clinical laboratory reference values for African adolescents and young adults that can be used in clinical trials and for patient management. METHODS AND FINDINGS: A panel of 298, HIV-seronegative individuals aged 13-34 years was randomly selected from participants in two population-based cross-sectional surveys assessing HIV prevalence and other sexually transmitted infections in western Kenya. The adolescent (<18 years)-to-adults (≥18 years) ratio and the male-to-female ratio was 1:1. Median and 95% reference ranges were calculated for immunohematological and biochemistry values. Compared with U.S-derived reference ranges, we detected lower hemoglobin (HB), hematocrit (HCT), red blood cells (RBC), mean corpuscular volume (MCV), neutrophil, glucose, and blood urea nitrogen values but elevated eosinophil and total bilirubin values. Significant gender variation was observed in hematological parameters in addition to T-bilirubin and creatinine indices in all age groups, AST in the younger and neutrophil, platelet and CD4 indices among the older age group. Age variation was also observed, mainly in hematological parameters among males. Applying U.S. NIH Division of AIDS (DAIDS) toxicity grading to our results, 40% of otherwise healthy study participants were classified as having an abnormal laboratory parameter (grade 1-4) which would exclude them from participating in clinical trials. CONCLUSION: Hematological and biochemistry reference values from African population differ from those derived from a North American population, showing the need to develop region-specific reference values. Our data also show variations in hematological indices between adolescent and adult males which should be considered when developing reference ranges. This study provides the first locally-derived clinical laboratory reference ranges for adolescents and young adults in western Kenya.

RATIONALE: Limited information exists on the prevalence of tuberculosis and adequacy of case finding in African populations with high HIV-prevalence. OBJECTIVE: To estimate the prevalence of bacteriologically confirmed pulmonary tuberculosis (PTB), the fraction attributable to HIV, and evaluate case detection. METHODS: Residents ≥15 years old, from 40 randomly sampled clusters, provided two sputum samples for microscopy; those with chest radiograph abnormalities or symptoms suggestive of PTB provided one additional sputum for culture. MEASUREMENTS: PTB was defined by a culture positive for M.tuberculosis or 2 positive smears. Persons with PTB were offered HIV-testing, and interviewed on care seeking behavior. We estimated the population attributable fraction of HIV on prevalent and notified PTB, the patient diagnostic rate (PDR), and case detection rate (CDR), using provincial TB notification data. MAIN RESULTS: Among 20,566 participants, 123 had PTB. TB prevalence was 6.0/1000 (95% CI 4.6-7.4) for all PTB and 2.5/1000 (1.6-3.4) for smear-positive PTB. Of 101 prevalent TB cases tested, 52 (51%) were HIV-infected, and 58 (64%) of 91 cases who were not on treatment and were interviewed had not sought care. Forty-eight percent of prevalent and 65% of notified PTB cases were attributable to HIV. For smear-positive and smear-negative PTB combined, the PDR was 1.4 cases detected per person-year among HIV-infected persons having PTB and 0.6 for HIV-uninfected, corresponding to CDRs of 56% and 65%, respectively. CONCLUSIONS: Undiagnosed PTB is common in this community. TB case finding needs improvement, through intensified case finding, rigorous HIV-testing, and improved diagnosis of smear-negative TB.

The $63 billion comprehensive global health initiative (GHI) emphasizes health systems strengthening (HSS) to tackle challenges, including child and maternal health, HIV/AIDS, family planning, and neglected tropical diseases. GHI and other initiatives are critical to fighting emerging and reemerging diseases in resource-poor countries. HSS is also an increasing focus of the $49 billion program of the US President's Emergency Plan for AIDS Relief and the Global Fund to Fight AIDS, Tuberculosis and Malaria. Laboratory systems and services are often neglected in resource-poor settings, but the funding offers an opportunity to end the neglect. To sustainably strengthen national laboratory systems in resource-poor countries, the following approaches are needed: (1) developing integrative national laboratory strategic plans and policies and building systems to address multiple diseases; (2) establishing public-private partnerships; (3) ensuring effective leadership, commitment, and coordination by host governments of efforts of donors and partners; (4) establishing and/or strengthening centers of excellence and field epidemiology and laboratory training programs to meet short- and medium-term training and retention goals; and (5) establishing affordable, scalable, and effective laboratory accreditation schemes to ensure quality of laboratory tests and bridge the gap between clinicians and laboratory experts on the use of test results.