Introducing www.epidemic-em.org: A Collection of Online Resources and Training Materials for Strengthening use of Emergency Operations Centers for Epidemic Response.

OBJECTIVE: This work aimed to demonstrate that a website, www.epidemic-em.org, encompassing "static" resources, and videos, as well as other tools, can be used to strengthen public health emergency management capacity during epidemic response. METHODS: Existing resources were updated and developed for self-directed Emergency Operations Centers' capacity strengthening, in order to encompass current best practices, and to emphasize how public health emergency management concepts can support epidemic response activities. These materials formed the core of the website, launched in June 2020, to which country case studies were added. In 2021, a pilot virtual training program was designed using recorded video lectures and interviews with global experts in addition to the website material, which was delivered to South African responders. RESULTS: The website has been accessed in more than 135 countries, demonstrating widespread reach and interest in online and freely accessible materials to support public health emergency operations. Over 30 people participated in the pilot virtual training, and the evaluation showed improvement in knowledge, confidence in using emergency management concepts for epidemic response, and positive feedback on the virtual modality. CONCLUSIONS: Online tools can expand access to materials and resources for public health emergency management capacity strengthening. Virtual modalities can further serve as a powerful complement, and perhaps replacement, for traditional in-person technical assistance, despite some limitations.

Trends in COVID-19 admissions and deaths among people living with HIV in South Africa: analysis of national surveillance data.

BACKGROUND: In 2021, the HIV prevalence among South African adults was 18% and more than 2 million people had uncontrolled HIV and, therefore, had increased risk of poor outcomes with SARS-CoV-2 infection. We investigated trends in COVID-19 admissions and factors associated with in-hospital COVID-19 mortality among people living with HIV and people without HIV. METHODS: In this analysis of national surveillance data, we linked and analysed data collected between March 5, 2020, and May 28, 2022, from the DATCOV South African national COVID-19 hospital surveillance system, the SARS-CoV-2 case line list, and the Electronic Vaccination Data System. All analyses included patients hospitalised with SARS-CoV-2 with known in-hospital outcomes (ie, who were discharged alive or had died) at the time of data extraction. We used descriptive statistics for admissions and mortality trends. Using post-imputation random-effect multivariable logistic regression models, we compared characteristics and the case fatality ratio of people with HIV and people without HIV. Using modified Poisson regression models, we compared factors associated with mortality among all people with COVID-19 admitted to hospital and factors associated with mortality among people with HIV. FINDINGS: Among 397 082 people with COVID-19 admitted to hospital, 301 407 (75·9%) were discharged alive, 89 565 (22·6%) died, and 6110 (1·5%) had no recorded outcome. 270 737 (68·2%) people with COVID-19 had documented HIV status (22 858 with HIV and 247 879 without). Comparing characteristics of people without HIV and people with HIV in each COVID-19 wave, people with HIV had increased odds of mortality in the D614G (adjusted odds ratio 1·19, 95% CI 1·09-1·29), beta (1·08, 1·01-1·16), delta (1·10, 1·03-1·18), omicron BA.1 and BA.2 (1·71, 1·54-1·90), and omicron BA.4 and BA.5 (1·81, 1·41-2·33) waves. Among all COVID-19 admissions, mortality was lower among people with previous SARS-CoV-2 infection (adjusted incident rate ratio 0·32, 95% CI 0·29-0·34) and with partial (0·93, 0·90-0·96), full (0·70, 0·67-0·73), or boosted (0·50, 0·41-0·62) COVID-19 vaccination. Compared with people without HIV who were unvaccinated, people without HIV who were vaccinated had lower risk of mortality (0·68, 0·65-0·71) but people with HIV who were vaccinated did not have any difference in mortality risk (1·08, 0·96-1·23). In-hospital mortality was higher for people with HIV with CD4 counts less than 200 cells per µL, irrespective of viral load and vaccination status. INTERPRETATION: HIV and immunosuppression might be important risk factors for mortality as COVID-19 becomes endemic. FUNDING: South African National Institute for Communicable Diseases, the South African National Government, and the United States Agency for International Development.

Changing Epidemiology of COVID-19 in Children and Adolescents Over Four Successive Epidemic Waves in South Africa, 2020-2022.

BACKGROUND: South Africa experienced four waves of SARS-CoV-2 infection, dominated by Wuhan-Hu, Beta, Delta, and Omicron (BA.1/BA.2). We describe the trends in SARS-CoV-2 testing, cases, admissions, and deaths among children and adolescents in South Africa over successive waves. METHODS: We analyzed national SARS-CoV-2 testing, case, and admissions data from March 2020 to February 2022 and estimated cumulative rates by age group for each endpoint. The severity in the third versus the fourth wave was assessed using multivariable logistic regression. RESULTS: Individuals ≤18 years comprised 35% (21,008,060/60,142,978) of the population but only 12% (424,394/3,593,644) of cases and 6% (26,176/451,753) of admissions. Among individuals ≤18 years, infants had the highest admission (505/100,000) rates. Testing, case, and admission rates generally increased successively in the second (Beta) and third (Delta) waves among all age groups. In the fourth (Omicron BA.1/BA.2) wave, the case rate dropped among individuals ≥1 year but increased among those <1 year. Weekly admission rates for children <1 year (169/100,000) exceeded rates in adults (124/100,000) in the fourth wave. The odds of severe COVID-19 in all admitted cases were lower in the fourth wave versus the third wave in each age group, but they were twice as high in admitted cases with at least one comorbidity than those without. CONCLUSIONS: The admission rate for children <5 years was higher in the fourth wave than in previous waves, but the overall outcomes were less severe. However, children with at least one comorbidity had increased odds of severe disease, warranting consideration of prioritizing this group for vaccination.

Trends in Cases, Hospitalizations, and Mortality Related to the Omicron BA.4/BA.5 Subvariants in South Africa.

BACKGROUND: In this study, we compared admission incidence risk and the risk of mortality in the Omicron BA.4/BA.5 wave to previous waves. METHODS: Data from South Africa's SARS-CoV-2 case linelist, national COVID-19 hospital surveillance system, and Electronic Vaccine Data System were linked and analyzed. Wave periods were defined when the country passed a weekly incidence of 30 cases/100 000 population. In-hospital case fatality ratios (CFRs) during the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves were compared using post-imputation random effect multivariable logistic regression models. RESULTS: The CFR was 25.9% (N = 37 538 of 144 778), 10.9% (N = 6123 of 56 384), and 8.2% (N = 1212 of 14 879) in the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves, respectively. After adjusting for age, sex, race, comorbidities, health sector, and province, compared with the Omicron BA.4/BA.5 wave, patients had higher risk of mortality in the Omicron BA.1/BA.2 wave (adjusted odds ratio [aOR], 1.3; 95% confidence interval [CI]: 1.2-1.4) and Delta wave (aOR, 3.0; 95% CI: 2.8-3.2). Being partially vaccinated (aOR, 0.9; 95% CI: .9-.9), fully vaccinated (aOR, 0.6; 95% CI: .6-.7), and boosted (aOR, 0.4; 95% CI: .4-.5) and having prior laboratory-confirmed infection (aOR, 0.4; 95% CI: .3-.4) were associated with reduced risks of mortality. CONCLUSIONS: Overall, admission incidence risk and in-hospital mortality, which had increased progressively in South Africa's first 3 waves, decreased in the fourth Omicron BA.1/BA.2 wave and declined even further in the fifth Omicron BA.4/BA.5 wave. Mortality risk was lower in those with natural infection and vaccination, declining further as the number of vaccine doses increased.

Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages compared to BA.1 and Delta in South Africa.

Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. Here, we use the presence/absence of the S-gene target as a proxy for SARS-CoV-2 variant/lineage for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We link national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assess severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR 1.24, 95% CI 0.98-1.55) and severe outcome (aOR 0.72, 95% CI 0.41-1.26) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 showed similar severity to the BA.1 lineage and continued to show reduced clinical severity compared to the Delta variant.

Methods for early characterisation of the severity and dynamics of SARS-CoV-2 variants: a population-based time series analysis in South Africa.

BACKGROUND: Assessment of disease severity associated with a novel pathogen or variant provides crucial information needed by public health agencies and governments to develop appropriate responses. The SARS-CoV-2 omicron variant of concern (VOC) spread rapidly through populations worldwide before robust epidemiological and laboratory data were available to investigate its relative severity. Here we develop a set of methods that make use of non-linked, aggregate data to promptly estimate the severity of a novel variant, compare its characteristics with those of previous VOCs, and inform data-driven public health responses. METHODS: Using daily population-level surveillance data from the National Institute for Communicable Diseases in South Africa (March 2, 2020, to Jan 28, 2022), we determined lag intervals most consistent with time from case ascertainment to hospital admission and within-hospital death through optimisation of the distance correlation coefficient in a time series analysis. We then used these intervals to estimate and compare age-stratified case-hospitalisation and case-fatality ratios across the four epidemic waves that South Africa has faced, each dominated by a different variant. FINDINGS: A total of 3 569 621 cases, 494 186 hospitalisations, and 99 954 deaths attributable to COVID-19 were included in the analyses. We found that lag intervals and disease severity were dependent on age and variant. At an aggregate level, fluctuations in cases were generally followed by a similar trend in hospitalisations within 7 days and deaths within 15 days. We noted a marked reduction in disease severity throughout the omicron period relative to previous waves (age-standardised case-fatality ratios were consistently reduced by >50%), most substantial for age strata with individuals 50 years or older. INTERPRETATION: This population-level time series analysis method, which calculates an optimal lag interval that is then used to inform the numerator of severity metrics including the case-hospitalisation and case-fatality ratio, provides useful and timely estimates of the relative effects of novel SARS-CoV-2 VOCs, especially for application in settings where resources are limited. FUNDING: National Institute for Communicable Diseases of South Africa, South African National Government.

Clinical severity of COVID-19 in patients admitted to hospital during the omicron wave in South Africa: a retrospective observational study.

BACKGROUND: Up to the end of January, 2022, South Africa has had four recognisable COVID-19 pandemic waves, each predominantly dominated by one variant of concern: the ancestral strain with an Asp614Gly mutation during the first wave, the beta variant (B.1.351) during the second wave, the delta variant (B.1.617.2) during the third wave, and lastly, the omicron variant (B.1.1.529) during the fourth wave. We aimed to assess the clinical disease severity of patients admitted to hospital with SARS-CoV-2 infection during the omicron wave and compare the findings with those of the preceding three pandemic waves in South Africa. METHODS: We defined the start and end of each pandemic wave as the crossing of the threshold of weekly incidence of 30 laboratory-confirmed SARS-CoV-2 cases per 100 000 population. Hospital admission data were collected through an active national COVID-19-specific surveillance programme. We compared disease severity across waves by post-imputation random effect multivariable logistic regression models. Severe disease was defined as one or more of the following: acute respiratory distress, receipt of supplemental oxygen or mechanical ventilation, admission to intensive care, or death. FINDINGS: We analysed 335 219 laboratory-confirmed SARS-CoV-2 hospital admissions with a known outcome, constituting 10·4% of 3 216 179 cases recorded during the four waves. During the omicron wave, 52 038 (8·3%) of 629 617 cases were admitted to hospital, compared with 71 411 (12·9%) of 553 530 in the Asp614Gly wave, 91 843 (12·6%) of 726 772 in the beta wave, and 131 083 (10·0%) of 1 306 260 in the delta wave (p<0·0001). During the omicron wave, 15 421 (33·6%) of 45 927 patients admitted to hospital had severe disease, compared with 36 837 (52·3%) of 70 424 in the Asp614Gly wave, 57 247 (63·4%) of 90 310 in the beta wave, and 81 040 (63·0%) of 128 558 in the delta wave (p<0·0001). The in-hospital case-fatality ratio during the omicron wave was 10·7%, compared with 21·5% during the Asp614Gly wave, 28·8% during the beta wave, and 26·4% during the delta wave (p<0·0001). Compared with those admitted to hospital during the omicron wave, patients admitted during the other three waves had more severe clinical presentations (adjusted odds ratio 2·07 [95% CI 2·01-2·13] in the Asp614Gly wave, 3·59 [3·49-3·70] in the beta wave, and 3·47 [3·38-3·57] in the delta wave). INTERPRETATION: The trend of increasing cases and admissions across South Africa's first three waves shifted in the omicron wave, with a higher and quicker peak but fewer patients admitted to hospital, less clinically severe illness, and a lower case-fatality ratio compared with the preceding three waves. Omicron marked a change in the SARS-CoV-2 epidemic curve, clinical profile, and deaths in South Africa. Extrapolations to other populations should factor in differing vaccination and previous infection levels. FUNDING: National Institute for Communicable Diseases.

Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa.

We provide two methods for monitoring reinfection trends in routine surveillance data to identify signatures of changes in reinfection risk and apply these approaches to data from South Africa's severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic to date. Although we found no evidence of increased reinfection risk associated with circulation of the Beta (B.1.351) or Delta (B.1.617.2) variants, we did find clear, population-level evidence to suggest immune evasion by the Omicron (B.1.1.529) variant in previously infected individuals in South Africa. Reinfections occurring between 1 November 2021 and 31 January 2022 were detected in individuals infected in all three previous waves, and there has been an increase in the risk of having a third infection since mid-November 2021.

Early assessment of the clinical severity of the SARS-CoV-2 omicron variant in South Africa: a data linkage study.

BACKGROUND: The SARS-CoV-2 omicron variant of concern was identified in South Africa in November, 2021, and was associated with an increase in COVID-19 cases. We aimed to assess the clinical severity of infections with the omicron variant using S gene target failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy. METHODS: We did data linkages for national, South African COVID-19 case data, SARS-CoV-2 laboratory test data, SARS-CoV-2 genome data, and COVID-19 hospital admissions data. For individuals diagnosed with COVID-19 via TaqPath PCR tests, infections were designated as either SGTF or non-SGTF. The delta variant was identified by genome sequencing. Using multivariable logistic regression models, we assessed disease severity and hospitalisations by comparing individuals with SGTF versus non-SGTF infections diagnosed between Oct 1 and Nov 30, 2021, and we further assessed disease severity by comparing SGTF-infected individuals diagnosed between Oct 1 and Nov 30, 2021, with delta variant-infected individuals diagnosed between April 1 and Nov 9, 2021. FINDINGS: From Oct 1 (week 39), 2021, to Dec 6 (week 49), 2021, 161 328 cases of COVID-19 were reported in South Africa. 38 282 people were diagnosed via TaqPath PCR tests and 29 721 SGTF infections and 1412 non-SGTF infections were identified. The proportion of SGTF infections increased from two (3·2%) of 63 in week 39 to 21 978 (97·9%) of 22 455 in week 48. After controlling for factors associated with hospitalisation, individuals with SGTF infections had significantly lower odds of admission than did those with non-SGTF infections (256 [2·4%] of 10 547 vs 121 [12·8%] of 948; adjusted odds ratio [aOR] 0·2, 95% CI 0·1-0·3). After controlling for factors associated with disease severity, the odds of severe disease were similar between hospitalised individuals with SGTF versus non-SGTF infections (42 [21%] of 204 vs 45 [40%] of 113; aOR 0·7, 95% CI 0·3-1·4). Compared with individuals with earlier delta variant infections, SGTF-infected individuals had a significantly lower odds of severe disease (496 [62·5%] of 793 vs 57 [23·4%] of 244; aOR 0·3, 95% CI 0·2-0·5), after controlling for factors associated with disease severity. INTERPRETATION: Our early analyses suggest a significantly reduced odds of hospitalisation among individuals with SGTF versus non-SGTF infections diagnosed during the same time period. SGTF-infected individuals had a significantly reduced odds of severe disease compared with individuals infected earlier with the delta variant. Some of this reduced severity is probably a result of previous immunity. FUNDING: The South African Medical Research Council, the South African National Department of Health, US Centers for Disease Control and Prevention, the African Society of Laboratory Medicine, Africa Centers for Disease Control and Prevention, the Bill & Melinda Gates Foundation, the Wellcome Trust, and the Fleming Fund.

A citywide, clonal outbreak of Pseudomonas aeruginosa.

BACKGROUND: Outbreaks of community-acquired Pseudomonas aeruginosa are typically small and localized. We investigated an increase in community-acquired infections with P. aeruginosa in Cape Town, South Africa. METHODS: Cases were defined as P. aeruginosa isolated from any clinical sample, and "wild-type" as those susceptible to all antibiotics tested. The residential addresses of community-acquired wild-type cases were mapped. Whole-genome sequencing and multilocus sequence typing were used to determine clonality and identify virulence genes. A clinical study in a subset of patients with bloodstream infection compared demographic and clinical characteristics between sequence types (STs). RESULTS: The outbreak lasted 10 months from December 2016 to September 2017 with 3,321 documented cases. At the peak, cases reached 2.3-fold baseline rates. Cases were distributed widely across the city. Multilocus ST 303 was predominant during the outbreak. A total of 51 virulence genes were differentially present in ST303 compared with other STs, including genes involved in biofilm formation, iron uptake, and gut penetration. CONCLUSION: The investigation confirmed a citywide outbreak of P. aeruginosa. We identified a predominant outbreak-associated clone, ST303, which harbored genes that could contribute to virulence and survival in adverse environmental conditions such as those associated with drought.

A systematic review on mobile health applications for foodborne disease outbreak management.

BACKGROUND: Foodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action. METHODS: Studies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases "OR" and "AND". Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management. RESULTS: Five hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown. CONCLUSIONS: There is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.

Genome Sequencing of a Severe Acute Respiratory Syndrome Coronavirus 2 Isolate Obtained from a South African Patient with Coronavirus Disease 2019.

As a contribution to the global efforts to track and trace the ongoing coronavirus pandemic, here we present the sequence, phylogenetic analysis, and modeling of nonsynonymous mutations for a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome that was detected in a South African patient with coronavirus disease 2019 (COVID-19).

Outbreak of Listeriosis in South Africa Associated with Processed Meat.

BACKGROUND: An outbreak of listeriosis was identified in South Africa in 2017. The source was unknown. METHODS: We conducted epidemiologic, trace-back, and environmental investigations and used whole-genome sequencing to type Listeria monocytogenes isolates. A case was defined as laboratory-confirmed L. monocytogenes infection during the period from June 11, 2017, to April 7, 2018. RESULTS: A total of 937 cases were identified, of which 465 (50%) were associated with pregnancy; 406 of the pregnancy-associated cases (87%) occurred in neonates. Of the 937 cases, 229 (24%) occurred in patients 15 to 49 years of age (excluding those who were pregnant). Among the patients in whom human immunodeficiency virus (HIV) status was known, 38% of those with pregnancy-associated cases (77 of 204) and 46% of the remaining patients (97 of 211) were infected with HIV. Among 728 patients with a known outcome, 193 (27%) died. Clinical isolates from 609 patients were sequenced, and 567 (93%) were identified as sequence type 6 (ST6). In a case-control analysis, patients with ST6 infections were more likely to have eaten polony (a ready-to-eat processed meat) than those with non-ST6 infections (odds ratio, 8.55; 95% confidence interval, 1.66 to 43.35). Polony and environmental samples also yielded ST6 isolates, which, together with the isolates from the patients, belonged to the same core-genome multilocus sequence typing cluster with no more than 4 allelic differences; these findings showed that polony produced at a single facility was the outbreak source. A recall of ready-to-eat processed meat products from this facility was associated with a rapid decline in the incidence of L. monocytogenes ST6 infections. CONCLUSIONS: This investigation showed that in a middle-income country with a high prevalence of HIV infection, L. monocytogenes caused disproportionate illness among pregnant girls and women and HIV-infected persons. Whole-genome sequencing facilitated the detection of the outbreak and guided the trace-back investigations that led to the identification of the source.

Human surveillance and phylogeny of highly pathogenic avian influenza A(H5N8) during an outbreak in poultry in South Africa, 2017.

BACKGROUND: In June 2017, an outbreak of the highly pathogenic avian influenza A(H5N8) was detected in commercial poultry farms in South Africa, which rapidly spread to all nine South African provinces. OBJECTIVES: We conducted active surveillance for the transmission of influenza A(H5N8) to humans working with infected birds during the South African outbreak. METHODS: Influenza A(H5N8)-positive veterinary specimens were used to evaluate the ability of real-time PCR-based assays to detect contemporary avian influenza A(H5N8) strains. Whole genome sequences were generated from these specimens by next-generation sequencing for phylogenetic characterization and screening for mammalian-adaptive mutations. RESULTS: Human respiratory samples from 74 individuals meeting our case definition, all tested negative for avian influenza A(H5) by real-time PCR, but 2 (3%) were positive for human influenza A(H3N2). 54% (40/74) reported wearing personal protective equipment including overalls, boots, gloves, masks, and goggles. 94% (59/63) of veterinary specimens positive for H5N8 were detected on an influenza A(H5) assay for human diagnostics. A commercial H5N8 assay detected H5 in only 6% (3/48) and N8 in 92% (44/48). Thirteen (13/25; 52%) A(H5N8) genomes generated from veterinary specimens clustered in a single monophyletic clade. These sequences contained the NS (P42S) and PB2 (L89V) mutations noted as markers of mammalian adaptation. CONCLUSIONS: Diagnostic assays were able to detect and characterize influenza A(H5N8) viruses, but poor performance is reported for a commercial assay. Absence of influenza A(H5N8) in humans with occupational exposure and no clear impression of molecular adaptation for mammalian infection suggest that this avian pathogen continues to be low-risk human pathogen.

Whole-Genome Sequences of Listeria monocytogenes Sequence Type 6 Isolates Associated with a Large Foodborne Outbreak in South Africa, 2017 to 2018.

We report whole-genome sequences for 10 Listeria monocytogenes sequence type 6 isolates associated with a large listeriosis outbreak in South Africa, which occurred over the period of 2017 to 2018. The possibility of listeriosis spreading beyond South Africa's borders as a result of exported contaminated food products prompted us to make the genome sequences publicly available.

Detection of Campylobacter species in stool specimens from patients with symptoms of acute flaccid paralysis in South Africa.

INTRODUCTION: Guillain-Barré Syndrome (GBS) is an autoimmune disease characterized by acute or subacute symmetrical ascending motor weakness, areflexia, and mild-to-moderate sensory abnormalities. Campylobacter jejuni is reported to be the most common bacterium associated with GBS cases. Despite the eradication of polio, the number of reported GBS cases remains considerably high in South Africa with the causative agents not being well described. METHODOLOGY: The aim of the study was to investigate the proportion of Campylobacter spp. detected in stool specimens from patients with symptoms of acute flaccid paralysis (AFP). Stool specimens from patients presenting with AFP, that were negative for polio and non-polio enteroviruses (NPENT), were processed and screened for the presence of Campylobacter spp. using quantitative PCR (qPCR). RESULTS: Of the 512 stool specimens screened between October 2014 to December 2015, 12% (62/512) were positive for Campylobacter spp. Of these 62 Campylobacter infections: 77.4% (48/62) was C. jejuni; 19.4% (12/62) was Campylobacter coli; 3.2% (2/62) was mixed infections of C. jejuni and C. coli. CONCLUSIONS: True association of the disease with Campylobacter spp. will enable the proportion of Campylobacter-induced GBS to be better described in South Africa; this can only be done through systematic studies that include bacterial culture and serology together with molecular methodologies.

Comparison of species-level identification and antifungal susceptibility results from diagnostic and reference laboratories for bloodstream Candida surveillance isolates, South Africa, 2009-2010.

From February 2009 through August 2010, we compared species-level identification of bloodstream Candida isolates and susceptibility to fluconazole, voriconazole, and caspofungin between diagnostic and reference South African laboratories during national surveillance for candidemia. Diagnostic laboratories identified isolates to genus/species level and performed antifungal susceptibility testing, as indicated. At a reference laboratory, viable Candida isolates were identified to species-level using automated systems, biochemical tests, or DNA sequencing; broth dilution susceptibility testing was performed. Categorical agreement (CA) was calculated for susceptibility results of isolates with concordant species identification. Overall, 2172 incident cases were detected, 773 (36%) by surveillance audit. The Vitek 2 YST system (bioMérieux Inc, Marcy l'Etoile, France) was used for identification (360/863, 42%) and susceptibility testing (198/473, 42%) of a large proportion of isolates. For the five most common species (n = 1181), species-level identification was identical in the majority of cases (Candida albicans: 98% (507/517); Candida parapsilosis: 92% (450/488); Candida glabrata: 89% (89/100); Candida tropicalis: 91% (49/54), and Candida krusei: 86% (19/22)). However, diagnostic laboratories were significantly less likely to correctly identify Candida species other than C. albicans versus C. albicans (607/664, 91% vs. 507/517, 98%; P < .001). Susceptibility data were compared for isolates belonging to the five most common species and fluconazole, voriconazole, and caspofungin in 860, 580, and 99 cases, respectively. Diagnostic laboratories significantly under-reported fluconazole resistance in C. parapsilosis (225/393, 57% vs. 239/393, 61%; P < .001) but over-reported fluconazole non-susceptibility in C. albicans (36/362, 10% vs. 3/362, 0.8%; P < .001). Diagnostic laboratories were less likely to correctly identify Candida species other than C. albicans, under-reported fluconazole resistance for C. parapsilosis and over-reported fluconazole resistance for C. albicans.