BackgroundTime series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.ResultsWe applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt.ConclusionsRandom Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.

ObjectivesNon-communicable diseases (NCDs) account for one-third of disability-adjusted life years in Malawi, and access to care is exceptionally limited. Integrated services with HIV are widely recommended, but few examples exist globally. We report descriptive outcomes from an Integrated Chronic Care Clinic (IC3).DesignThis is a retrospective cohort study.SettingThe study includes an HIV–NCD clinic across 14 primary care facilities in the rural district of Neno, Malawi.ParticipantsAll new patients, including 6233 HIV–NCD diagnoses, enrolled between January 2015 and December 2017 were included. This included 3334 patients with HIV (59.7% women) and 2990 patients with NCD (67.3% women), 10% overall under age 15 years.InterventionsPatients were seen at their nearest health centre, with a hospital team visiting routinely to reinforce staffing. Data were collected on paper forms and entered into an electronic medical record.Primary and secondary outcome measuresRoutine clinical measurements are reported at 1-year post-enrolment for patients with more than one visit. One-year retention is reported by diagnosis.ResultsNCD diagnoses were 1693 hypertension, 668 asthma, 486 epilepsy, 149 diabetes and 109 severe mental illness. By December 2018, 8.3% of patients with NCD over 15 years were also on HIV treatment. One-year retention was 85% for HIV and 72% for NCDs, with default in 8.4% and 25.5% and deaths in 4.0% and 1.4%, respectively. Clinical outcomes showed statistically significant improvement for hypertension, diabetes, asthma and epilepsy. Of the 1807 (80%) of patients with HIV with viral load results, 85% had undetectable viral load.ConclusionsThe IC3 model, built on an HIV platform, facilitated rapid decentralisation and access to NCD services in rural Malawi. Clinical outcomes and retention in care are favourable, suggesting that integration of chronic disease care at the primary care level poses a way forward for the large dual burden of HIV and chronic NCDs.

Objectives:To determine the incidence and risk factors of mortality for all HIV-infected patients receiving antiretroviral treatment at public and private healthcare facilities in the Botswana National HIV/AIDS Treatment Programme.Design:We studied routinely collected data from 226 030 patients enrolled in the Botswana National HIV/AIDS Treatment Programme from 2002 to 2013.Methods:A person-years (P-Y) approach was used to analyse all-cause mortality and follow-up rates for all HIV-infected individuals with documented antiretroviral therapy initiation dates. Marginal structural modelling was utilized to determine the effect of treatment on survival for those with documented drug regimens. Sensitivity analyses were performed to assess the robustness of our results.Results:Median follow-up time was 37 months (interquartile range 11–75). Mortality was highest during the first 3 months after treatment initiation at 11.79 (95% confidence interval 11.49–12.11) deaths per 100 P-Y, but dropped to 1.01 (95% confidence interval 0.98–1.04) deaths per 100 P-Y after the first year of treatment. Twelve-month mortality declined from 7 to 2% of initiates during 2002–2012. Tenofovir was associated with lower mortality than stavudine and zidovudine.Conclusion:The observed mortality rates have been declining over time; however, mortality in the first year, particularly first 3 months of antiretroviral treatment, remains a distinct problem. This analysis showed lower mortality with regimens containing tenofovir compared with zidovudine and stavudine. CD4+ cell count less than 100 cells/μl, older age and being male were associated with higher odds of mortality.

Molecular phylogenetic relationships within the Chlorophyta have relied heavily on rRNA data. These data have revolutionized our insight in green algal evolution, yet some class relationships have never been well resolved. A commonly used class within the Chlorophyta is the Ulvophyceae, although there is not much support for its monophyly. The relationships among the Ulvophyceae, Trebouxiophyceae, and Chlorophyceae are also contentious. In recent years, chloroplast genome data have shown their utility in resolving relationships between the main green algal clades, but such studies have never included marine macroalgae. We provide partial chloroplast genome data (∼30,000 bp, 23 genes) of the ulvophycean macroalga Caulerpa filiformis (Suhr) K. Herig. We show gene order conservation for some gene combinations and rearrangements in other regions compared to closely related taxa. Our data also revealed a pseudogene (ycf62) in Caulerpa species. Our phylogenetic results, based on analyses of a 23-gene alignment, suggest that neither Ulvophyceae nor Trebouxiophyceae are monophyletic, with Caulerpa being more closely related to the trebouxiophyte Chlorella than to Oltmannsiellopsis and Pseudendoclonium.

Objective To evaluate the variation in all-cause attrition (mortality and loss to follow-up (LTFU)) among HIV-infected individuals in Botswana by health district during the rapid and massive scale-up of the National Treatment Program. Methods Analysis of routinely collected longitudinal data from 226,030 patients who received ART through the Botswana National HIV/AIDS Treatment Program across all 24 health districts from 2002 to 2013. A time-to-event analysis was used to measure crude mortality and loss to follow-up rates (LTFU). A marginal structural model was used to evaluate mortality and LTFU rates by district over time, adjusted for individual-level risk factors (e.g., age, gender, baseline CD4, year of treatment initiation, and antiretroviral regimen). Results Mortality rates in the districts ranged from the lowest 1.0 (95% CI 0.9–1.1) in Selibe-Phikwe, to the highest 5.0 (95% CI 4.0–6.1), in Mabutsane. There was a wide range of overall LTFU across districts, including rates as low as 4.6 (95% CI 4.4–4.9) losses per 100 person-years in Ngamiland, and 5.9 (95% CI 5.6–6.2) losses per 100 person-years in South East, to rates as high as 25.4 (95% CI 23.08–27.89) losses per 100 person-years in Mabutsane and 46.3 (95% CI 43.48–49.23) losses per 100 person-years in Okavango. Even when known risk factors for mortality and LTFU were adjusted for, district was a significant predictor of both mortality and LTFU rates Conclusion We found statistically significant variation in attrition (mortality and LTFU) and data quality among districts. These findings suggest that district-level contextual factors affect retention in treatment. Further research needs to investigate factors that can potentially cause this variation.