Mapping local variation in household overcrowding across Africa from 2000 to 2018: a modelling study.

BACKGROUND: Household overcrowding is a serious public health threat associated with high morbidity and mortality. Rapid population growth and urbanisation contribute to overcrowding and poor sanitation in low-income and middle- income countries, and are risk factors for the spread of infectious diseases, including COVID-19, and antimicrobial resistance. Many countries do not have adequate surveillance capacity to monitor household overcrowding. Geostatistical models are therefore useful tools for estimating household overcrowding. In this study, we aimed to estimate household overcrowding in Africa between 2000 and 2018 by combining available household survey data, population censuses, and other country-specific household surveys within a geostatistical framework. METHODS: We used data from household surveys and population censuses to generate a Bayesian geostatistical model of household overcrowding in Africa for the 19-year period between 2000 and 2018. Additional sociodemographic and health-related covariates informed the model, which covered 54 African countries. FINDINGS: We analysed 287 surveys and population censuses, covering 78 695 991 households. Spatial and temporal variability arose in household overcrowding estimates over time. In 2018, the highest overcrowding estimates were observed in the Horn of Africa region (median proportion 62% [IQR 57-63]); the lowest regional median proportion was estimated for the north of Africa region (16% [14-19]). Overall, 474·4 million (95% uncertainty interval [UI] 250·1 million-740·7 million) people were estimated to be living in overcrowded conditions in Africa in 2018, a 62·7% increase from the estimated 291·5 million (180·8 million-417·3 million) people who lived in overcrowded conditions in the year 2000. 48·5% (229·9 million) of people living in overcrowded conditions came from six African countries (Nigeria, Ethiopia, Democratic Republic of the Congo, Sudan, Uganda, and Kenya), with a combined population of 538·3 million people. INTERPRETATION: This study incorporated survey and population censuses data and used geostatistical modelling to estimate continent-wide overcrowding over a 19-year period. Our analysis identified countries and areas with high numbers of people living in overcrowded conditions, thereby providing a benchmark for policy planning and the implementation of interventions such as in infectious disease control. FUNDING: UK Department of Health and Social Care, Wellcome Trust, Bill & Melinda Gates Foundation.

Global antibiotic consumption and usage in humans, 2000-18: a spatial modelling study.

BACKGROUND: Antimicrobial resistance (AMR) is a serious threat to global public health. WHO emphasises the need for countries to monitor antibiotic consumption to combat AMR. Many low-income and middle-income countries (LMICs) lack surveillance capacity; we aimed to use multiple data sources and statistical models to estimate global antibiotic consumption. METHODS: In this spatial modelling study, we used individual-level data from household surveys to inform a Bayesian geostatistical model of antibiotic usage in children (aged <5 years) with lower respiratory tract infections in LMICs. Antibiotic consumption data were obtained from multiple sources, including IQVIA, WHO, and the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). The estimates of the antibiotic usage model were used alongside sociodemographic and health covariates to inform a model of total antibiotic consumption in LMICs. This was combined with a single model of antibiotic consumption in high-income countries to produce estimates of antibiotic consumption covering 204 countries and 19 years. FINDINGS: We analysed 209 surveys done between 2000 and 2018, covering 284 045 children with lower respiratory tract infections. We identified large national and subnational variations of antibiotic usage in LMICs, with the lowest levels estimated in sub-Saharan Africa and the highest in eastern Europe and central Asia. We estimated a global antibiotic consumption rate of 14·3 (95% uncertainty interval 13·2-15·6) defined daily doses (DDD) per 1000 population per day in 2018 (40·2 [37·2-43·7] billion DDD), an increase of 46% from 9·8 (9·2-10·5) DDD per 1000 per day in 2000. We identified large spatial disparities, with antibiotic consumption rates varying from 5·0 (4·8-5·3) DDD per 1000 per day in the Philippines to 45·9 DDD per 1000 per day in Greece in 2018. Additionally, we present trends in consumption of different classes of antibiotics for selected Global Burden of Disease study regions using the IQVIA, WHO, and ESAC-net input data. We identified large increases in the consumption of fluoroquinolones and third-generation cephalosporins in North Africa and Middle East, and south Asia. INTERPRETATION: To our knowledge, this is the first study that incorporates antibiotic usage and consumption data and uses geostatistical modelling techniques to estimate antibiotic consumption for 204 countries from 2000 to 2018. Our analysis identifies both high rates of antibiotic consumption and a lack of access to antibiotics, providing a benchmark for future interventions. FUNDING: Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill & Melinda Gates Foundation.

Drug-resistant enteric fever worldwide, 1990 to 2018: a systematic review and meta-analysis.

BACKGROUND: Antimicrobial resistance (AMR) is an increasing threat to global health. There are > 14 million cases of enteric fever every year and > 135,000 deaths. The disease is primarily controlled by antimicrobial treatment, but this is becoming increasingly difficult due to AMR. Our objectives were to assess the prevalence and geographic distribution of AMR in Salmonella enterica serovars Typhi and Paratyphi A infections globally, to evaluate the extent of the problem, and to facilitate the creation of geospatial maps of AMR prevalence to help targeted public health intervention. METHODS: We performed a systematic review of the literature by searching seven databases for studies published between 1990 and 2018. We recategorised isolates to allow the analysis of fluoroquinolone resistance trends over the study period. The prevalence of multidrug resistance (MDR) and fluoroquinolone non-susceptibility (FQNS) in individual studies was illustrated by forest plots, and a random effects meta-analysis was performed, stratified by Global Burden of Disease (GBD) region and 5-year time period. Heterogeneity was assessed using the I2 statistics. We present a descriptive analysis of ceftriaxone and azithromycin resistance. FINDINGS: We identified 4557 articles, of which 384, comprising 124,347 isolates (94,616 S. Typhi and 29,731 S. Paratyphi A) met the pre-specified inclusion criteria. The majority (276/384; 72%) of studies were from South Asia; 40 (10%) articles were identified from Sub-Saharan Africa. With the exception of MDR S. Typhi in South Asia, which declined between 1990 and 2018, and MDR S. Paratyphi A, which remained at low levels, resistance trends worsened for all antimicrobials in all regions. We identified several data gaps in Africa and the Middle East. Incomplete reporting of antimicrobial susceptibility testing (AST) and lack of quality assurance were identified. INTERPRETATION: Drug-resistant enteric fever is widespread in low- and middle-income countries, and the situation is worsening. It is essential that public health and clinical measures, which include improvements in water quality and sanitation, the deployment of S. Typhi vaccination, and an informed choice of treatment are implemented. However, there is no licenced vaccine for S. Paratyphi A. The standardised reporting of AST data and rollout of external quality control assessment are urgently needed to facilitate evidence-based policy and practice. TRIAL REGISTRATION: PROSPERO CRD42018029432.

Cross-Reactivity and Anti-viral Function of Dengue Capsid and NS3-Specific Memory T Cells Toward Zika Virus.

Zika virus (ZIKV), a flavivirus with homology to dengue virus (DENV), is spreading to areas of DENV hyper-endemicity. Heterologous T cell immunity, whereby virus-specific memory T cells are activated by variant peptides derived from a different virus, can lead to enhanced viral clearance or diminished protective immunity and altered immunopathology. In mice, CD8+ T cells specific for DENV provide in vivo protective efficacy against subsequent ZIKV infection. In humans, contrasting studies report complete absence or varying degrees of DENV/ZIKV T cell cross-reactivity. Moreover, the impact of cross-reactive T cell recognition on the anti-viral capacity of T cells remains unclear. Here, we show that DENV-specific memory T cells display robust cross-reactive recognition of ZIKV NS3 ex vivo and after in vitro expansion in respectively n = 7/10 and n = 9/9 dengue-immune individuals tested. In contrast, cross-reactivity toward ZIKV capsid is low or absent. Cross-reactive recognition of DENV or ZIKV NS3 peptides elicits similar production of the anti-viral effector mediators IFN-γ, TNF-α, and CD107a. We identify 9 DENV/ZIKV cross-reactive epitopes, 7 of which are CD4+ and 2 are CD8+ T cell epitopes. We also show that cross-reactive CD4+ and CD8+ T cells targeting novel NS3 epitopes display anti-viral effector potential toward ZIKV-infected cells, with CD8+ T cells mediating direct lyses of these cells. Our results demonstrate that DENV NS3-specific memory T cells display anti-viral effector capacity toward ZIKV, suggesting a potential beneficial effect in humans of pre-existing T cell immunity to DENV upon ZIKV infection.

Dengue knowledge, attitudes and practices and their impact on community-based vector control in rural Cambodia.

BACKGROUND: Globally there are an estimated 390 million dengue infections per year, of which 96 million are clinically apparent. In Cambodia, estimates suggest as many as 185,850 cases annually. The World Health Organization global strategy for dengue prevention aims to reduce mortality rates by 50% and morbidity by 25% by 2020. The adoption of integrated vector management approach using community-based methods tailored to the local context is one of the recommended strategies to achieve these objectives. Understanding local knowledge, attitudes and practices is therefore essential to designing suitable strategies to fit each local context. METHODS AND FINDINGS: A Knowledge, Attitudes and Practices survey in 600 randomly chosen households was administered in 30 villages in Kampong Cham which is one of the most populated provinces of Cambodia. KAP surveys were administered to a sub-sample of households where an entomology survey was conducted (1200 households), during which Aedes larval/pupae and adult female Aedes mosquito densities were recorded. Participants had high levels of knowledge regarding the transmission of dengue, Aedes breeding, and biting prevention methods; the majority of participants believed they were at risk and that dengue transmission is preventable. However, self-reported vector control practices did not match observed practices recorded in our surveys. No correlation was found between knowledge and observed practices either. CONCLUSION: An education campaign regarding dengue prevention in this setting with high knowledge levels is unlikely to have any significant effect on practices unless it is incorporated in a more comprehensive strategy for behavioural change, such a COMBI method, which includes behavioural models as well as communication and marketing theory and practice. TRIAL REGISTRATION: ISRCTN85307778.

Virus-specific T lymphocytes home to the skin during natural dengue infection.

Dengue, which is the most prevalent mosquito-borne viral disease afflicting human populations, causes a spectrum of clinical symptoms that include fever, muscle and joint pain, maculopapular skin rash, and hemorrhagic manifestations. Patients infected with dengue develop a broad antigen-specific T lymphocyte response, but the phenotype and functional properties of these cells are only partially understood. We show that natural infection induces dengue-specific CD8(+) T lymphocytes that are highly activated and proliferating, exhibit antiviral effector functions, and express CXCR3, CCR5, and the skin-homing marker cutaneous lymphocyte-associated antigen (CLA). In the same patients, bystander human cytomegalovirus -specific CD8(+) T cells are also activated during acute dengue infection but do not express the same tissue-homing phenotype. We show that CLA expression by circulating dengue-specific CD4(+) and CD8(+) T cells correlates with their in vivo ability to traffic to the skin during dengue infection. The juxtaposition of dengue-specific T cells with virus-permissive cell types at sites of possible dengue exposure represents a previously uncharacterized form of immune surveillance for this virus. These findings suggest that vaccination strategies may need to induce dengue-specific T cells with similar homing properties to provide durable protection against dengue viruses.

Defining CD8+ T cell determinants during human viral infection in populations of Asian ethnicity.

The identification of virus-specific CD8(+) T cell determinants is a fundamental requirement for our understanding of viral disease pathogenesis. T cell epitope mapping strategies increasingly rely on algorithms that predict the binding of peptides to MHC molecules. There is, however, little information on the reliability of predictive algorithms in the context of human populations, in particular, for those expressing HLA class I molecules for which there are limited experimental data available. In this study, we evaluate the ability of NetMHCpan to predict antiviral CD8(+) T cell epitopes that we identified with a traditional approach in patients of Asian ethnicity infected with Dengue virus, hepatitis B virus, or severe acute respiratory syndrome coronavirus. We experimentally demonstrate that the predictive power of algorithms defining peptide-MHC interaction directly correlates with the amount of training data on which the predictive algorithm has been constructed. These results highlight the limited applicability of the NetMHCpan algorithm for populations expressing HLA molecules for which there are little or no experimental binding data, such as those of Asian ethnicity.

Differential targeting of viral components by CD4+ versus CD8+ T lymphocytes in dengue virus infection.

Dengue virus (DENV) is the principal arthropod-borne viral pathogen afflicting human populations. While repertoires of antibodies to DENV have been linked to protection or enhanced infection, the role of T lymphocytes in these processes remains poorly defined. This study provides a comprehensive overview of CD4(+) and CD8(+) T cell epitope reactivities against the DENV 2 proteome in adult patients experiencing secondary DENV infection. Dengue virus-specific T cell responses directed against an overlapping 15mer peptide library spanning the DENV 2 proteome were analyzed ex vivo by enzyme-linked immunosorbent spot assay, and recognition of individual peptides was further characterized in specific T cell lines. Thirty novel T cell epitopes were identified, 9 of which are CD4(+) and 21 are CD8(+) T cell epitopes. We observe that whereas CD8(+) T cell epitopes preferentially target nonstructural proteins (NS3 and NS5), CD4(+) epitopes are skewed toward recognition of viral components that are also targeted by B lymphocytes (envelope, capsid, and NS1). Consistently, a large proportion of dengue virus-specific CD4(+) T cells have phenotypic characteristics of circulating follicular helper T cells (CXCR5 expression and production of interleukin-21 or gamma interferon), suggesting that they are interacting with B cells in vivo. This study shows that during a dengue virus infection, the protein targets of human CD4(+) and CD8(+) T cells are largely distinct, thus highlighting key differences in the immunodominance of DENV proteins for these two cell types. This has important implications for our understanding of how the two arms of the human adaptive immune system are differentially targeted and employed as part of our response to DENV infection.