Incidence Estimates of Acute Q Fever and Spotted Fever Group Rickettsioses, Kilimanjaro, Tanzania, from 2007 to 2008 and from 2012 to 2014

Q fever and spotted fever group rickettsioses (SFGR) are common causes of severe febrile illness in northern Tanzania. Incidence estimates are needed to characterize the disease burden. Using hybrid surveillance—coupling case-finding at two referral hospitals and healthcare utilization data—we estimated the incidences of acute Q fever and SFGR in Moshi, Kilimanjaro, Tanzania, from 2007 to 2008 and from 2012 to 2014. Cases were defined as fever and a four-fold or greater increase in antibody titers of acute and convalescent paired sera according to the indirect immunofluorescence assay of Coxiella burnetii phase II antigen for acute Q fever and Rickettsia conorii (2007–2008) or Rickettsia africae (2012–2014) antigens for SFGR. Healthcare utilization data were used to adjust for underascertainment of cases by sentinel surveillance. For 2007 to 2008, among 589 febrile participants, 16 (4.7%) of 344 and 27 (8.8%) of 307 participants with paired serology had Q fever and SFGR, respectively. Adjusted annual incidence estimates of Q fever and SFGR were 80 (uncertainty range, 20–454) and 147 (uncertainty range, 52–645) per 100,000 persons, respectively. For 2012 to 2014, among 1,114 febrile participants, 52 (8.1%) and 57 (8.9%) of 641 participants with paired serology had Q fever and SFGR, respectively. Adjusted annual incidence estimates of Q fever and SFGR were 56 (uncertainty range, 24–163) and 75 (uncertainty range, 34–176) per 100,000 persons, respectively. We found substantial incidences of acute Q fever and SFGR in northern Tanzania during both study periods. To our knowledge, these are the first incidence estimates of either disease in sub-Saharan Africa. Our findings suggest that control measures for these infections warrant consideration.

Measurement report: Characterization of uncertainties in fluxes and fuel sulfur content from ship emissions in the Baltic Sea

Fluxes of gaseous compounds and nanoparticles were studied using micrometeorological methods at Harmaja in the Baltic Sea. The measurement site was situated beside the ship route to and from the city of Helsinki. The gradient (GR) method was used to measure fluxes of SO2, NO, NO2, O3, CO2, and Ntot (the number concentration of nanoparticles). In addition, the flux of CO2 was also measured using the eddy-covariance (EC) method. Distortion of the flow field caused by obstacles around the measurement mast was studied by applying a computation fluid dynamic (CFD) model. This was used to establish the corresponding heights in the undisturbed stream. The wind speed and the turbulent parameters at each of the established heights were then recalculated for the gradient model. The effect of waves on the boundary layer was taken into consideration, as the Monin–Obukhov theory used to calculate the fluxes is not valid in the presence of swell. Uncertainty budgets for the measurement systems were constructed to judge the reliability of the results. No clear fluxes across the air–sea nor the sea–air interface were observed for SO2, NO, NO2, NOx (= NO + NO2), O3, or CO2 using the GR method. A negative flux was observed for Ntot, with a median value of −0.23 × 109 m−2 s−1 and an uncertainty range of 31 %–41 %. For CO2, while both positive and negative fluxes were observed, the median value was −0.081 μmol m−2 s−1 with an uncertainty range of 30 %–60 % for the EC methods. Ship emissions were responsible for the deposition of Ntot, while they had a minor effect on CO2 deposition. The fuel sulfur content (FSC) of the marine fuel used in ships passing the site was determined from the observed ratio of the SO2 and CO2 concentrations. A typical value of 0.40 ± 0.06 % was obtained for the FSC, which is in compliance with the contemporary FSC limit value of 1 % in the Baltic Sea area at the time of measurements. The method to estimate the uncertainty in the FSC was found to be accurate enough for use with the latest regulations, 0.1 % (Baltic Sea area) and 0.5 % (global oceans).

The Integration of Analytical P/Z Material Balance Method with Static Modeling and Integrated Asset Model IAM to Generate Reliable Forecasting for a Giant Onshore Gas Field in Abu Dhabi

FGIIP (Field Gas Initially in Place) is one of the most essential elements in building dependable static and Integrated Asset Model (IAM). A good estimation of FGIIP will improve history matching and generate reliable forecast. The mature gas field producing under depletion mode is an ideal example where P/Z technique can fit well to re-estimate the FGIIP. Even more, the estimation is also important to narrow down FGIIP uncertainties that initially existed in static model. Reliable FGIIP estimation is achieved by performing multiple P/Z calculations. The process involves dividing reservoir into key areas and each area is represented by individual P/Z prior to summing-up all P/Z to get the total FGIIP. Several scenarios are developed by defining key areas based on permeability variation, areal distribution and PVT behavior. The best FGIIP estimation is then fed back into the static model to generate numerous realizations considering the static uncertainties to produce the same FGIIP. Static models with realistic distribution of properties and good history match are used in the IAM model to generate forecast. The giant onshore gas field is highly heterogeneous having permeability, lateral composition variation and dynamic interaction between wells. To ensure that the heterogeneity observed in the field is honored, multiple key areas are defined by making areal sectorization and lateral PVT variation when estimating FGIIP with P/Z approach. Communication between areas was evidenced from the sectoral P/Z. The field history matching was improved after applying the new estimated FGIIP. It was observed that the sectoral history matching both for production and pressure matches from some selected realizations built in static model resulted in better matches. Succinctly the re-evaluation of static derived FGIIP with P/Z method for the mature gas field was able to reduce the uncertainty range that initially existed. Incorporating the correct estimation of FGIIP in IAM has helped to yield reliable forecast and has enabled the asset to plan proper work programs for further field development. Analytical material balance with P/Z is very applicable for mature gas reservoirs producing under depletion mode. The approach is worth doing to narrow down the uncertainty range that was previously calculated. Moreover, the integration of analytical P/Z with static and dynamic model (IAM) has achieved more reliable forecasting of the mature gas field to proceed with further development plan.

Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2

As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2—the receptor of SARS-CoV-2 in human cells—and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8–3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19.

Isoniazid or rifampicin preventive therapy with and without screening for subclinical TB: a modeling analysis

Background Short-course, rifamycin-based regimens could facilitate scale-up of tuberculosis preventive therapy (TPT), but it is unclear how stringently tuberculosis (TB) disease should be ruled out before TPT use. Methods We developed a state-transition model of a TPT intervention among two TPT-eligible cohorts: adults newly diagnosed with HIV in South Africa (PWH) and TB household contacts in Pakistan (HHCs). We modeled two TPT regimens—4 months of rifampicin [4R] or 6 months of isoniazid [6H]—comparing each to a reference of no intervention. Before initiating TPT, TB disease was excluded either through symptom-only screening or with additional radiographic screening that could detect subclinical TB but might limit access to the TPT intervention. TPT’s potential curative effects on both latent and subclinical TB were modeled, as were both acquisitions of resistance and prevention of drug-resistant disease. Although all eligible individuals received the screening and/or TPT interventions, the modeled TB outcomes comprised only those with latent or subclinical TB that would have progressed to symptomatic disease if untreated. Results When prescribed after only symptom-based TB screening (such that individuals with subclinical TB were included among TPT recipients), 4R averted 45 active (i.e., symptomatic) TB cases (95% uncertainty range 24–79 cases or 40–89% of progressions to active TB) per 1000 PWH [17 (9–29, 43–94%) per 1000 HHCs]; 6H averted 37 (19–66, 52–73%) active TB cases among PWH [13 (7–23, 53–75%) among HHCs]. With this symptom-only screening, for each net rifampicin resistance case added by 4R, 12 (3–102) active TB cases were averted among PWH (37 [9–580] among HHCs); isoniazid-resistant TB was also reduced. Similarly, 6H after symptom-only screening increased isoniazid resistance while reducing overall and rifampicin-resistant active TB. Screening for subclinical TB before TPT eliminated this net increase in resistance to the TPT drug; however, if the screening requirement reduced TPT access by more than 10% (the estimated threshold for 4R among HHCs) to 30% (for 6H among PWH), it was likely to reduce the intervention’s overall TB prevention impact. Conclusions All modeled TPT strategies prevent TB relative to no intervention, and differences between TPT regimens or between screening approaches are small relative to uncertainty in the outcomes of any given strategy. If most TPT-eligible individuals can be screened for subclinical TB, then pairing such screening with rifamycin-based TPT maximizes active TB prevention and does not increase rifampicin resistance. Where subclinical TB cannot be routinely excluded without substantially reducing TPT access, the choice of TPT regimen requires weighing 4R’s efficacy advantages (as well as its greater safety and shorter duration that we did not directly model) against the consequences of rifampicin resistance in a small fraction of recipients.

New Concepts about DOL-DFL Nexus: The Relationships with Market Sensitivities, Firm-Specific Risk and Other Issues

This paper investigates several issues related to the Degree of Operating Leverage (DOL) and the Degree of Financial Leverage (DFL) in the light of advanced concepts on the matter proposed by recent studies. In particular, the paper treats mainly the relationships between DOL and market sensitivities and the impact of the uncertainty on DOL and DFL volatility together with minor issues. We used the DOL function already developed to analyse what market conditions facilitate or hinder, with or without economies of scale, Revenue development or a profit-maximising policy. DOL records the reaction coming from the factor and product markets together with the management decision process. DOL highlights whether the current economic strategy is, or not, successful and why, so that management can perceive clues to evaluate both the policy and its implementation. The uncertainty related to six fundamental economic variables determining EBIT and Net Profit growth volatility eventually contaminates DOL and DFL. Not all such variables impact DOL and DFL volatility, but when it happens, the firm’s risk is representable through the asymptotes of the DOL and DFL curves generated by each specific variable. Such a risk rate is independent of the chosen uncertainty range and is firm unique in any financial period. In normal economic conditions, DOL undervalues firm-specific risk while DFL carries out a containment function. The higher risk rate comes from the unit price change, that coupled with a sturdy quantity/mix growth, could induce negative economic and financial results.

Manuscript Title: Unlocking New/Missed Reservoir Zones at Shallow Depth Based on Integrating Post-Hydraulic Fracture Performance with Reservoir, Petrophysics, and Geology Data

Skhidno-Poltavske Field is a Ukrainian gas field producing mostly from commingled wells. These commingled wells have no information about the production split and the pressure data measured for each formation separately. This was one of the main challenges to study the field and understand the potential of each individual formation. Many wells were hydraulically fractured (HF) and showed a wide range of production and pressure performance after the stimulation. Six of these HF wells showed atypical pressure and production behavior after the HF compared to the rest of the wells. The main challenge in the reservoir simulation study was to understand whether these HFs reached isolated lateral segments of the same producing zones or accessed other reservoir zones by/due to vertical propagation of the hydraulic fracture plane. Understanding the pressure and production performance of these wells and comparing them to the other wells was the key to revealing their behavior. This was integrated with the petrophysical data to understand the potential formations and the uncertainty range of their properties. The geomodeling was the destination to translate these uncertainties into different realizations that were all dynamically tested to generate the most probable realization. The integration between different domains resulted in unlocking an overlooked productive zone that was out of consideration. This increased the reserves of this field and extended its life. One of the study recommendations was to test and develop this formation through perforating the existing wells or drilling new wells targeting the overlooked productive zone.

Using precipitation sensitivity to temperature to adjust projected global runoff

Climate change affects the water cycle. Despite the improved accuracy of simulations of historical temperature, precipitation and runoff in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6), the uncertainty of the future sensitivity of global runoff to temperature remains large. Here, we identify a statistical relationship at the global scale between the sensitivity of precipitation to temperature change (1979 – 2014) and the sensitivity of runoff to temperature change (2015 – 2100). We use this relation to constrain future runoff sensitivity estimates. Our statistical relationship only slightly reduces the uncertainty range of future runoff sensitivities (order 10% reduction). However, more importantly, it raises the expected global runoff sensitivity to background global warming by 36-104% compared to estimates taken directly from the CMIP6 model ensemble. The constrained sensitivities also indicate a shift towards globally more wet conditions and less dry conditions.

Weather Variability Induced Uncertainty of Contrail Radiative Forcing

Persistent contrails and contrail cirrus are estimated to have a larger impact on climate than all CO2 emissions from global aviation since the introduction of jet engines. However, the measure for this impact, the effective radiative forcing (ERF) or radiative forcing (RF), suffers from uncertainties that are much larger than those for CO2. Despite ongoing research, the so called level of scientific understanding has not improved since the 1999 IPCC Special Report on Aviation and the Global Atmosphere. In this paper, the role of weather variability as a major component of the uncertainty range of contrail cirrus RF is examined. Using 10 years of MOZAIC flights and ERA-5 reanalysis data, we show that natural weather variability causes large variations in the instantaneous radiative forcing (iRF) of persistent contrails, which is a major source for uncertainty. Most contrails (about 80%) have a small positive iRF of up to 20 W m−2. IRF exceeds 20 W m−2 in about 10% of all cases but these have a disproportionally large climate impact, the remaining 10% have a negative iRF. The distribution of iRF values is heavily skewed towards large positive values that show an exponential decay. Monte Carlo experiments reveal the difficulty of determining a precise long-term mean from measurement or campaign data alone. Depending on the chosen sample size, calculated means scatter considerably, which is caused exclusively by weather variability. Considering that many additional natural sources of variation have been deliberately neglected in the present examination, the results suggest that there is a fundamental limit to the precision with which the RF and ERF of contrail cirrus can be determined. In our opinion, this does not imply a low level of scientific understanding; rather the scientific understanding of contrails and contrail cirrus has grown considerably over recent decades. Only the determination of global and annual mean RF and ERF values is still difficult and will probably be so for the coming decades, if not forever. The little precise knowledge of the RF and ERF values is, therefore, no argument to postpone actions to mitigate contrail’s warming impact.

Forced convection heat transfer characteristics of Al2O3 nanofluids in a minichannel - an experimental study

In this study, an experimental investigation on the convective heat transfer characteristics of Al2O3 nanofluids flowing through an horizontal minichannel under the laminar and turbulent flow and constant heat flux conditions is performed. Several sample nanofluids were prepared using two base fluids (water and the mixture 80/20 DW/EG vol.%) and several low concentrations of Al2O3 nanoparticles ranging from 0.01 to 0.1 vol%. An existing experimental setup was modified for this study. The measurements were taken for the base fluid and nanofluids at each flow and heating conditions. The results are analyzed in terms of Nu and friction factor (f) in comparison with those of the base fluid. The results demonstrate that the used low concentrations of Al2O3 nanoparticles are not enough to yield any noticeable enhancement in heat transfer of the nanofluid samples. The deviations between the results of the nanofluids and the base fluid are small and within the uncertainty range of the experimental setup.