Nevin Manimala

PLoS One. 2021 May 20;16(5):e0251403. doi: 10.1371/journal.pone.0251403. eCollection 2021.

ABSTRACT

Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.

PMID:34014989 | DOI:10.1371/journal.pone.0251403

PLoS One. 2021 May 20;16(5):e0251742. doi: 10.1371/journal.pone.0251742. eCollection 2021.

ABSTRACT

BACKGROUND: This study provides detailed characteristics of vector populations in preparation for a three-arm cluster randomized controlled trial (RCT) aiming to compare the community impact of dual active-ingredient (AI) long-lasting insecticidal nets (LLINs) that combine two novel insecticide classes-chlorfenapyr or pyriproxifen-with alpha-cypermethrin to improve the prevention of malaria transmitted by insecticide-resistant vectors compared to standard pyrethroid LLINs.

METHODS: The study was carried out in 60 villages across Cove, Zangnanando and Ouinhi districts, southern Benin. Mosquito collections were performed using human landing catches (HLCs). After morphological identification, a sub-sample of Anopheles gambiae s.l. were dissected for parity, analyzed by PCR for species and presence of L1014F kdr mutation and by ELISA-CSP to identify Plasmodium falciparum sporozoite infection. WHO susceptibility tube tests were performed by exposing adult An. gambiae s.l., collected as larvae from each district, to 0.05% alphacypermethrin, 0.75% permethrin, 0.1% bendiocarb and 0.25% pirimiphos-methyl. Synergist assays were also conducted with exposure first to 4% PBO followed by alpha-cypermethrin.

RESULTS: An. gambiae s.l. (n = 10807) was the main malaria vector complex found followed by Anopheles funestus s.l. (n = 397) and Anopheles nili (n = 82). An. gambiae s.l. was comprised of An. coluzzii (53.9%) and An. gambiae s.s. (46.1%), both displaying a frequency of the L1014F kdr mutation >80%. Although more than 80% of people slept under standard LLIN, human biting rate (HBR) in An. gambiae s.l. was higher indoors [26.5 bite/person/night (95% CI: 25.2-27.9)] than outdoors [18.5 b/p/n (95% CI: 17.4-19.6)], as were the trends for sporozoite rate (SR) [2.9% (95% CI: 1.7-4.8) vs 1.8% (95% CI: 0.6-3.8)] and entomological inoculation rate (EIR) [21.6 infected bites/person/month (95% CI: 20.4-22.8) vs 5.4 (95% CI: 4.8-6.0)]. Parous rate was 81.6% (95%CI: 75.4-88.4). An. gambiae s.l. was resistant to alpha-cypermethrin and permethrin but, fully susceptible to bendiocarb and pirimiphos-methyl. PBO pre-exposure followed by alpha-cypermethrin treatment induced a higher 24 hours mortality compared to alphacypermethrin alone but not exceeding 40%.

CONCLUSIONS: Despite a high usage of standard pyrethroid LLINs, the study area is characterized by intense malaria transmission. The main vectors An. coluzzii and An. gambiae s.s. were both highly resistant to pyrethroids and displayed multiple resistance mechanisms, L1014F kdr mutation and mixed function oxidases. These conditions of the study area make it an appropriate site to conduct the trial that aims to assess the effect of novel dual-AI LLINs on malaria transmitted by insecticide-resistant vectors.

PMID:34014982 | DOI:10.1371/journal.pone.0251742

PLoS One. 2021 May 20;16(5):e0251776. doi: 10.1371/journal.pone.0251776. eCollection 2021.

ABSTRACT

Steep canyons surrounded by high mountains resulting from large-scale landslides characterize the study area located in the southeastern part of the Tibetan Plateau. A total of 1766 large landslides were identified based on integrated remote sensing interpretations utilizing multisource satellite images and topographic data that were dominated by 3 major regional categories, namely, rockslides, rock falls, and flow-like landslides. The geographical detector method was applied to quantitatively unveil the spatial association between the landslides and 12 environmental factors through computation of the q values based on spatially stratified heterogeneity. Meanwhile, a certainty factor (CF) model was used for comparison. The results indicate that the q values of the 12 influencing factors vary obviously, and the dominant factors are also different for the 3 types of landslides, with annual mean precipitation (AMP) being the dominant factor for rockslide distribution, elevation being the dominant factor for rock fall distribution and lithology being the dominant factor for flow-like distribution. Integrating the results of the factor detector and ecological detector, the AMP, annual mean temperature (AMT), elevation, river density, fault distance and lithology have a stronger influence on the spatial distribution of landslides than other factors. Furthermore, the factor interactions can significantly enhance their interpretability of landslides, and the top 3 dominant interactions were revealed. Based on statistics of landslide discrepancies with respect to diverse stratification of each factor, the high-risk zones were identified for 3 types of landslides, and the results were contrasted with the CF model. In conclusion, our method provides an objective framework for landslide prevention and mitigation through quantitative, spatial and statistical analyses in regions with complex terrain.

PMID:34014965 | DOI:10.1371/journal.pone.0251776

PLoS One. 2021 May 20;16(5):e0251427. doi: 10.1371/journal.pone.0251427. eCollection 2021.

ABSTRACT

BACKGROUND: Little research has explored the influence of social context on health of Indian adolescents. We conceptualized community-level women’s education (proxy for value placed on women’s wellbeing) as exerting contextual influence on adolescent hemoglobin level and body mass index (BMI).

METHODS: We derived our sample of more than 62,000 adolescent aged 15 through 17 years from the Indian National Family Health Survey 2015-16. The sample consisted of a total of 62648 adolescents (54232 girls and 8416 boys) for the hemoglobin, and 62846 adolescents (54383 girls and 8463 boys) for the BMI analysis. We fitted multilevel random intercepts linear regression models to test the association of village- and urban-ward-level-women’s education with hemoglobin level and BMI of adolescents, accounting for their own and their mother’s education; as well as relevant covariates.

FINDINGS: Our fully adjusted model estimated that if the 52% of communities with less than 20 percent of women having a tenth-grade education in our sample were to achieve 100 percent tenth-grade completion in women, hemoglobin would be 0·2 g/dl higher (p<0·001) and BMI would be 0·62 kg/m2 higher on average among all adolescents in such communities. Unexplained variance estimates at the contextual level remained statistically significant, indicating the importance of context on adolescent undernutrition.

INTERPRETATIONS: Adolescents are deeply embedded in their context, influenced by contextual factors affecting health. Promoting adolescent health therefore implies altering social norms related to adolescent health and health behaviors; along with structural changes creating a health-promoting environment. Integrating our empirical findings with theoretically plausible pathways connecting community-level women’s education with adolescent undernutrition, we suggest that enhancing community-level women’s education beyond high school is necessary to facilitate these processes.

IMPLICATIONS: Addressing contextual determinants of adolescent undernutrition might be the missing link in India’s adolescent anemia and undernutrition prevention efforts, which are currently focused heavily on individual-level biomedical determinants of the problem.

PMID:34014954 | DOI:10.1371/journal.pone.0251427

PLoS One. 2021 May 20;16(5):e0239793. doi: 10.1371/journal.pone.0239793. eCollection 2021.

ABSTRACT

MOTIVATION: Local protein structure is usually described via classifying each peptide to a unique class from a set of pre-defined structures. These classifications may differ in the number of structural classes, the length of peptides, or class attribution criteria. Most methods that predict the local structure of a protein from its sequence first rely on some classification and only then proceed to the 3D conformation assessment. However, most classification methods rely on homologous proteins’ existence, unavoidably lose information by attributing a peptide to a single class or suffer from a suboptimal choice of the representative classes.

RESULTS: To alleviate the above challenges, we propose a method that constructs a peptide’s structural representation from the sequence, reflecting its similarity to several basic representative structures. For 5-mer peptides and 16 representative structures, we achieved the Q16 classification accuracy of 67.9%, which is higher than what is currently reported in the literature. Our prediction method does not utilize information about protein homologues but relies only on the amino acids’ physicochemical properties and the resolved structures’ statistics. We also show that the 3D coordinates of a peptide can be uniquely recovered from its structural coordinates, and show the required conditions under various geometric constraints.

PMID:34014953 | DOI:10.1371/journal.pone.0239793

PLoS One. 2021 May 20;16(5):e0251242. doi: 10.1371/journal.pone.0251242. eCollection 2021.

ABSTRACT

The SARS-CoV-2 pandemic led to closure of nearly all K-12 schools in the United States of America in March 2020. Although reopening K-12 schools for in-person schooling is desirable for many reasons, officials understand that risk reduction strategies and detection of cases are imperative in creating a safe return to school. Furthermore, consequences of reclosing recently opened schools are substantial and impact teachers, parents, and ultimately educational experiences in children. To address competing interests in meeting educational needs with public safety, we compare the impact of physical separation through school cohorts on SARS-CoV-2 infections against policies acting at the level of individual contacts within classrooms. Using an age-stratified Susceptible-Exposed-Infected-Removed model, we explore influences of reduced class density, transmission mitigation, and viral detection on cumulative prevalence. We consider several scenarios over a 6-month period including (1) multiple rotating cohorts in which students cycle through in-person instruction on a weekly basis, (2) parallel cohorts with in-person and remote learning tracks, (3) the impact of a hypothetical testing program with ideal and imperfect detection, and (4) varying levels of aggregate transmission reduction. Our mathematical model predicts that reducing the number of contacts through cohorts produces a larger effect than diminishing transmission rates per contact. Specifically, the latter approach requires dramatic reduction in transmission rates in order to achieve a comparable effect in minimizing infections over time. Further, our model indicates that surveillance programs using less sensitive tests may be adequate in monitoring infections within a school community by both keeping infections low and allowing for a longer period of instruction. Lastly, we underscore the importance of factoring infection prevalence in deciding when a local outbreak of infection is serious enough to require reverting to remote learning.

PMID:34014947 | DOI:10.1371/journal.pone.0251242

PLoS Med. 2021 May 20;18(5):e1003571. doi: 10.1371/journal.pmed.1003571. eCollection 2021 May.

ABSTRACT

BACKGROUND: Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics.

METHODS AND FINDINGS: In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

CONCLUSIONS: In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

PMID:34014945 | DOI:10.1371/journal.pmed.1003571

PLoS One. 2021 May 20;16(5):e0247289. doi: 10.1371/journal.pone.0247289. eCollection 2021.

ABSTRACT

Philippine garlic (Allium sativum L.) is arguably known to pack flavor and aroma in smaller bulbs compared to imported varieties saturating the local market. In this study, ethanolic extracts of Philippine garlic cultivars were profiled using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF). γ-Glu dipeptides, oligosaccharides and lipids were determined in Philippine garlic cultivars through bioinformatics analysis in GNPS Molecular Networking Platform and fragmentation analysis. Multivariate statistical analysis using XCMS Online showed the abundance of γ-Glu allyl cysteine in Batanes-sourced garlic while γ-Glu propenyl cysteine, γ-Glu methyl cysteine, and alliin are enriched in the Ilocos cultivar. Principal component analysis showed that the γ-Glu dipeptides found in local garlic influenced their distinct separation across PC1 from imported varieties. This presence of high levels of γ-Glu dipeptides and probiotic oligosaccharides may potentially contribute to the superior flavor and nutritional benefits of Philippine garlic.

PMID:34014935 | DOI:10.1371/journal.pone.0247289

MMWR Morb Mortal Wkly Rep. 2021 May 21;70(20):765. doi: 10.15585/mmwr.mm7020a4.

NO ABSTRACT

PMID:34014912 | DOI:10.15585/mmwr.mm7020a4

J Biopharm Stat. 2021 May 20:1-2. doi: 10.1080/10543406.2021.1928833. Online ahead of print.

NO ABSTRACT

PMID:34014125 | DOI:10.1080/10543406.2021.1928833