COVID-19 in Japan: insights from the first three months of the epidemic

Background Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. Methods We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. Results The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ±2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95%CrI:1.6, 3.3) nationally. In the final week of the trusted period, Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6) respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients <20 years old developing pneumonia or severe respiratory symptoms. Conclusions Information collected in the early phases of an outbreak are important in characterising any novel pathogen. Timely recognition of key symptoms and high-risk settings for transmission can help to inform response strategies. The data analysed here were the result of robust and timely investigations and demonstrate the improvements to epidemic control as a result of such surveillanc

A Research Agenda for Helminth Diseases of Humans: Modelling for Control and Elimination

Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches

Neglected Tropical Diseases in Sub-Saharan Africa: Review of Their Prevalence, Distribution, and Disease Burden

The neglected tropical diseases (NTDs) are the most common conditions affecting the poorest 500 million people living in sub-Saharan Africa (SSA), and together produce a burden of disease that may be equivalent to up to one-half of SSA's malaria disease burden and more than double that caused by tuberculosis. Approximately 85% of the NTD disease burden results from helminth infections. Hookworm infection occurs in almost half of SSA's poorest people, including 40–50 million school-aged children and 7 million pregnant women in whom it is a leading cause of anemia. Schistosomiasis is the second most prevalent NTD after hookworm (192 million cases), accounting for 93% of the world's number of cases and possibly associated with increased horizontal transmission of HIV/AIDS. Lymphatic filariasis (46–51 million cases) and onchocerciasis (37 million cases) are also widespread in SSA, each disease representing a significant cause of disability and reduction in the region's agricultural productivity. There is a dearth of information on Africa's non-helminth NTDs. The protozoan infections, human African trypanosomiasis and visceral leishmaniasis, affect almost 100,000 people, primarily in areas of conflict in SSA where they cause high mortality, and where trachoma is the most prevalent bacterial NTD (30 million cases). However, there are little or no data on some very important protozoan infections, e.g., amebiasis and toxoplasmosis; bacterial infections, e.g., typhoid fever and non-typhoidal salmonellosis, the tick-borne bacterial zoonoses, and non-tuberculosis mycobaterial infections; and arboviral infections. Thus, the overall burden of Africa's NTDs may be severely underestimated. A full assessment is an important step for disease control priorities, particularly in Nigeria and the Democratic Republic of Congo, where the greatest number of NTDs may occur

Joint estimation of CD4+ cell progression and survival in untreated individuals with HIV-1 infection.

OBJECTIVE: We compiled the largest dataset of seroconverter cohorts to date from 25 countries across Africa, North America, Europe, and Southeast/East (SE/E) Asia to simultaneously estimate transition rates between CD4 cell stages and death, in antiretroviral therapy (ART)-naive HIV-1-infected individuals. DESIGN: A hidden Markov model incorporating a misclassification matrix was used to represent natural short-term fluctuations and measurement errors in CD4 cell counts. Covariates were included to estimate the transition rates and survival probabilities for each subgroup. RESULTS: The median follow-up time for 16 373 eligible individuals was 4.1 years (interquartile range 1.7-7.1), and the mean age at seroconversion was 31.1 years (SD 8.8). A total of 14 525 individuals had recorded CD4 cell counts pre-ART, 1885 died, and 6947 initiated ART. Median (interquartile range) survival for men aged 20 years at seroconversion was 13.0 (12.4-13.4), 11.6 (10.9-12.3), and 8.3 years (7.9-8.9) in Europe/North America, Africa, and SE/E Asia, respectively. Mortality rates increase with age (hazard ratio 2.22, 95% confidence interval 1.84-2.67 for >45 years compared with <25 years) and vary by region (hazard ratio 2.68, 1.75-4.12 for Africa and 1.88, 1.50-2.35 for Asia compared with Europe/North America). CD4 cell decline was significantly faster in Asian cohorts compared with Europe/North America (hazard ratio 1.45, 1.36-1.54). CONCLUSION: Mortality and CD4 cell progression rates exhibited regional and age-specific differences, with decreased survival in African and SE/E Asian cohorts compared with Europe/North America and in older age groups. This extensive dataset reveals heterogeneities between regions and ages, which should be incorporated into future HIV models

Estimating HIV incidence from surveillance data indicates a second wave of infections in Brazil

Emerging evidence suggests that HIV incidence rates in Brazil, particularly among men, may be rising. Here we use Brazil’s integrated health systems data to develop a mathematical model, reproducing the complex surveillance systems and providing estimates of HIV incidence, number of people living with HIV (PLHIV), reporting rates and ART initiation rates. An age-structured deterministic model with a flexible spline was used to describe the natural history of HIV along with reporting and treatment rates. Individual-level surveillance data for 1,077,295 cases (HIV/AIDS diagnoses, ART dispensations, CD4 counts and HIV/AIDS-related deaths) were used to calibrate the model using Bayesian inference. The results showed a second wave of infections occurring after 2001 and 56,000 (95% Credible Interval 43,000–71,000) new infections in 2015, 37,000 (95% CrI 28,000–54,000) infections in men and 16,000 (95% CrI 10,000–23,000) in women. The estimated number of PLHIV by end-2015 was 838,000 (95% CrI 675,000–1,083,000), with 80% (95% CrI 62–98%) of those individuals reported to the Ministry of Health. Women were more likely to be diagnosed and reported than men; 86.8% of infected women had been reported compared with 75.7% of men. Likewise, ART initiation rates for women were higher than those for men. The second wave contradicts previous estimates of HIV incidence trends in Brazil and there were persistent differences in the rates of accessing care between men and women. Nevertheless, the Brazilian HIV program has achieved high rates of detection and treatment, making considerable progress over the past ten years

Spatial dynamics and high risk transmission pathways of poliovirus in Nigeria 2001-2013

The polio eradication programme in Nigeria has been successful in reducing incidence to just six confirmed cases in 2014 and zero to date in 2015, but prediction and management of future outbreaks remains a concern. A Poisson mixed effects model was used to describe poliovirus spread between January 2001 and November 2013, incorporating the strength of connectivity between districts (local government areas, LGAs) as estimated by three models of human mobility: simple distance, gravity and radiation models. Potential explanatory variables associated with the case numbers in each LGA were investigated and the model fit was tested by simulation. Spatial connectivity, the number of non-immune children under five years old, and season were associated with the incidence of poliomyelitis in an LGA (all P < 0.001). The best-fitting spatial model was the radiation model, outperforming the simple distance and gravity models (likelihood ratio test P < 0.05), under which the number of people estimated to move from an infected LGA to an uninfected LGA was strongly associated with the incidence of poliomyelitis in that LGA. We inferred transmission networks between LGAs based on this model and found these to be highly local, largely restricted to neighbouring LGAs (e.g. 67.7% of secondary spread from Kano was expected to occur within 10 km). The remaining secondary spread occurred along routes of high population movement. Poliovirus transmission in Nigeria is predominantly localised, occurring between spatially contiguous areas. Outbreak response should be guided by knowledge of high-probability pathways to ensure vulnerable children are protected